Morris Infotech

MORRIS INFOTECH / AT A GLANCE

2024

Year founded

2.4

Years active

20+

Projects delivered

75%+

Client return rate

11+

Engineers & specialists

Core service lines

We started Morris Infotech in 2024 because growing businesses deserve engineering that ships, not slide decks. We pair AI with solid cloud, software and data foundations, and judge every project by an outcome.

Since launch, our team of 11+ engineers, designers and marketers has delivered 20+ projects across retail, healthcare, manufacturing and education, and more than three-quarters of our clients come back for a second build.

In-house engineers, no hand-offs. The people who scope your system build it and support it. Nothing is subcontracted.
Scoped before you commit. You get a clear cost, timeline and projected return after discovery, before any code is written.
Accountable after launch. We monitor, tune and fix what we build, with defined support and response times.

Who we are

A small, senior studio that builds AI-first software.

Morris Infotech is a team of engineers, designers and marketers. We started in 2024 on one idea: businesses should work directly with the people who build their systems.

Today our team covers AI and automation, web and mobile, cloud and data, design and growth, so most projects never need anyone outside the team.

What we doAI agents, chatbots, automation, custom software and data foundations.

Who we serveGrowing businesses across retail, healthcare, manufacturing and education.

How we workScoped up front, built in-house and supported after launch.

Our values

What we hold ourselves to.

These are the standards behind every scope, build and support call.

01Outcomes over outputWe judge every project by the result it delivers, not by the hours or features inside it.

02Senior hands on every buildThe people who scope your system build and support it. Nothing is subcontracted.

03Honest scopingYou get a clear cost, timeline and projected return before any code is written.

04Accountable after launchWe monitor, tune and fix what we ship, and report on it in plain language.

05Responsible AIHuman review, answers linked to their sources and guardrails on anything customer-facing.

06Always learningAI moves fast. We test new tools on real work and keep only what earns its place.

Careers

Want to build with us?

We hire people who like owning an outcome from first call to launch. See what we are looking for.

Join our team Talk to us

AI services

Seven ways we put AI to work.

Start with the problem you feel most. Each service pairs a plain-English fix with the outcome it is measured against.

AI Agent DevelopmentHours disappear into work a well-built agent finishes in seconds. We build the agents that give those hours back.

Hours disappear into work a well-built agent finishes in seconds. We build the agents that give those hours back to your team.

WHAT YOU GET

Fewer tier-1 tickets reaching your team, measured against a baseline we agree in week one
Agents trained on your data, your tone and your edge cases, not generic templates
Built into your own tools, so you are not renting seats on yet another platform

Build your AI agent Learn more →

AI Chatbot DevelopmentGeneric chatbots frustrate customers and dent your brand. A bot trained on your own policies and tone answers like your best agent.

Generic chatbots frustrate customers and dent your brand. A chatbot trained on your own policies, catalogue and tone answers the way your best agent would.

WHAT YOU GET

Website and WhatsApp bots that answer only from your approved content
A hand-off to a human, with the full conversation, when the bot is unsure
Leads qualified and pushed into your CRM or helpdesk

Build your chatbot Learn more →

AI AutomationYour team copies data between tabs, chases approvals and reformats reports. Automation takes the repetitive steps and leaves the decisions to people.

Your team copies data between tabs, chases approvals and reformats reports. Automation takes the repetitive steps off their plate and keeps a human on the decisions.

WHAT YOU GET

n8n and Python workflows across the tools you already use
Approvals, reminders and reports that run on their own schedule
Every run logged, so you can see what happened and why

Automate a workflow Learn more →

AI Voice AgentMissed calls cost deals and goodwill. A voice agent picks up every call, qualifies the caller and books the next step.

Missed calls cost deals and goodwill. A voice agent picks up every call, qualifies the caller and books the next step, then passes anything complex to your team.

WHAT YOU GET

Calls answered at any hour, in the languages you choose
Bookings and callbacks written straight into your calendar or CRM
Call summaries and transcripts your team can search

Build a voice agent Learn more →

Generative AI DevelopmentOff-the-shelf AI tools do not know your business. Custom generative apps turn your own documents into answers your team can trust.

Off-the-shelf AI tools do not know your business. Custom generative apps turn your own documents and data into drafts, answers and insight your team can trust.

WHAT YOU GET

Retrieval over your documents, so every answer points to its source
Drafting, summarising and extraction tools for repeat tasks
Guardrails and evaluation, so quality is measured rather than assumed

Build a GenAI app Learn more →

Data EngineeringYour data sits in a dozen tools and nobody trusts the numbers. We build pipelines that clean, join and refresh it in one place.

Your data sits in a dozen tools and nobody trusts the numbers. We build pipelines that clean, join and refresh it, so every report starts from one source.

WHAT YOU GET

Connectors and pipelines from your apps, sheets and databases
Quality checks that flag bad data before it reaches a dashboard
Power BI and analytics views on top, refreshed on schedule

Fix my data Learn more →

AI ConsultingYou know AI matters but not where to start. We assess your operations, rank the opportunities by return and hand you a plan.

You know AI matters but not where to start. We assess your operations, rank the opportunities by return and hand you a plan you can act on.

WHAT YOU GET

A workflow and data audit across your team
Opportunities ranked by effort, risk and projected return
A scoped first build you can approve, or take elsewhere

Book a readiness call Learn more →

AI & intelligent solutions

Custom agents and n8n workflows trained on your own data. They handle tier-1 work end to end and pass edge cases to your team.

Custom AI assistants & chatbots
n8n workflow automation
Operational intelligence & reporting

View details → 02

Cloud infrastructure

Secure hosting, networking and backups, so models and automations stay fast, resilient and cost-controlled in production.

Cloud setup & migration (AWS, Azure)
Networking & high availability
Monitoring, backups & security

View details → 03

Web & mobile app development

Web and mobile front-ends for your agents and data, shipped with a support plan from day one.

Websites, portals & dashboards
iOS & Android apps (Flutter)
E-commerce & app store launch

View details → 04

Custom software & ERP

ERP and operations tools shaped around how you run, with automation and AI assist where it saves hours.

Inventory & billing systems
HR & payroll tools
Workflow automation

View details → 05

DevOps

Automated pipelines, containers and monitoring that make every release fast, repeatable and reversible.

CI/CD pipelines
Docker & Kubernetes
Monitoring & incident response

View details → 06

UI/UX product design

Interfaces for agents and dashboards, prototyped and tested with real users before build.

Wireframes & prototypes
Design systems
Usability testing

View details → 07

IT support & consulting

Maintenance, security reviews and AI roadmapping for teams without an in-house CTO.

Maintenance plans
Security reviews
Technology roadmapping

View details → 08

Data analytics & reporting

Pipelines and analytics that turn scattered sheets and systems into decision-ready numbers.

Data cleaning & pipelines
KPI tracking & reporting
Predictive & trend analysis

View details → 09

Power BI dashboards

Live Power BI dashboards on your existing systems, refreshed on schedule, so leadership sees what matters as it happens.

Power BI dashboard builds
Data source integration
Scheduled refresh & alerts

View details → 10

Digital marketing

SEO, content and campaigns that bring the right audience to the products we build.

Search engine optimisation
Content & social strategy
Performance tracking & reporting

View details →

Built for your industry

Every industry has workflows an agent can own.

From healthcare and fintech to travel and hospitality, we learn how your sector really runs, then build the AI around it. Not listed? We will still build it.

HealthcareAgents for patient intake, scheduling and records, so your staff can focus on patients. SaaSIn-app support, onboarding and ticket triage agents built on your own docs. FintechKYC checks, regulatory monitoring and case handling, with a person making every final call. eCommerceOrder status, returns and product advice across WhatsApp, email and chat. eSportsCommunity moderation, player support and tournament operations, running around the clock. GCCArabic and English agents for support, paperwork and tenders, with region-based hosting. TravelTrip quoting, changes and disruption handling, so travellers get help in seconds. HospitalityReservations, guest concierge and housekeeping requests, handled 24/7 in your brand voice.

Why Morris

AI and data that work on a Monday morning.

Direct & reachable

Talk directly to the engineers building your system, not an account manager.

Data handled carefully

Access control, backups and secure hosting on every project by default.

Built to scale

Architecture decisions made for your business in three years, not just at launch.

Support that responds

A named engineer for every account, with clear response times.

What's included

01
Business websites & portalsFast, responsive sites and logged-in portals for customers, partners and staff, with search and assistants that answer from your own content.
02
Admin dashboardsBack-office screens to manage orders, content, users and reports in one place, with alerts for what needs attention.
03
E-commerce platformsCatalogues, carts and payments set up around how you sell, with recommendations and support automation on top.
04
Maintainable codeClean structure, automated tests and a proper handover, so the platform keeps growing with you.

Tools we use

FRONT END

ReactNext.jsTypeScriptTailwind CSSHTML / CSS

BACK END

Node.jsExpressPython (FastAPI)Java (Spring Boot)

DATABASES

PostgreSQLMongoDBRedis

PAYMENTS & COMMERCE

RazorpayStripeWooCommerceShopify

TESTING & DELIVERY

Git & GitHubJestPlaywrightDockerGitHub Actions

What's included

01
iOS & Android appsPolished apps for customers or field staff, with push notifications and offline support where it matters.
02
Cross-platform with FlutterOne codebase for both platforms, so features ship together and maintenance costs stay down.
03
Prototype to launchA clickable prototype first, then fortnightly builds you can install and test on your own phone.
04
App store launch supportStore listings, review submissions, crash reporting and a post-launch support window.

Tools we use

APP

FlutterDartRiverpodBloc

BACK END & APIS

Node.jsREST APIsPostgreSQLMongoDB

SERVICES

Firebase AuthPush notificationsCrashlyticsGoogle MapsRazorpay

DESIGN

Figma

RELEASE

App Store ConnectGoogle Play ConsoleTestFlightGitHub Actions

What's included

01
Inventory & billing systemsStock, orders, invoicing and tax-ready billing in one place, replacing spreadsheets from day one.
02
HR & payroll toolsAttendance, leave and payroll that match your policies, with approvals handled automatically.
03
Workflow automationApprovals, reminders and hand-offs run by n8n workflows, with a log of every step.
04
Reports that matterLive reports and Power BI views of the numbers owners actually check each morning.

Tools we use

CORE

Java (Spring Boot)Node.jsPython

INTERFACE

ReactTailwind CSS

DATABASES

PostgreSQLMySQLRedis

AUTOMATION

n8nPython scriptsWebhooks

REPORTING

Power BISQL viewsExcel / CSV export

INTEGRATIONS

REST APIsRazorpayWhatsApp Business APITally import / export

What we deliver

Infrastructure your team can trust.

From first design to day-to-day operations, one team owns the whole stack.

Cloud architecture and migrationA right-sized design on AWS or Azure, and a planned move from servers or another host with a tested cutover.

Networking and high availabilityPrivate networks, load balancing and multi-zone setups so one failure does not take you offline.

Managed databases and storageManaged PostgreSQL, MySQL and object storage with encryption, replicas and tested restores.

Infrastructure as codeEnvironments defined in Terraform, reviewed like application code and rebuildable on demand.

Monitoring, logging and alertsUptime, errors, latency and cost in one view, with alerts that reach the right person.

Security and access controlLeast-privilege roles, secrets management, network rules, WAF and encrypted data.

Backups and disaster recoveryAutomated backups, a written restore plan and recovery drills you can rely on.

Cost optimisationRight-sizing, budgets and alerts so the cloud bill stops surprising you.

Reference architecture

A typical production setup.

We adapt this to your traffic, compliance needs and budget.

How it works

From audit to steady operations.

01AssessWe review your current hosting, deployments, costs and risks, and agree what good looks like.

02DesignYou get an architecture, a cost estimate and a migration plan you can approve before we build.

03Build and migrateWe build in code, test under load and cut over in a planned window with a rollback ready.

04Operate and improveWe monitor, patch and tune each month, and report on uptime, incidents and spend.

Tools we use

Proven, widely supported tooling.

Cloud platforms

AWSMicrosoft AzureEC2S3RDSLambdaCloudFrontApp ServiceBlob StorageAzure SQL

Infrastructure as code

TerraformCloudFormationAnsible

Monitoring

PrometheusGrafanaCloudWatchAzure MonitorSentry

Edge and security

CloudflareNginxWAFIAMSecrets ManagerLet's Encrypt

Data and backup

PostgreSQLMySQLMongoDBRedisAutomated snapshots

Ways to work with us

Start small or hand it over.

Cloud reviewA fixed-scope audit of your hosting, security and spend, with a prioritised fix list.

Migration projectMove to AWS or Azure with a tested plan, a staged cutover and a rollback path.

Managed operationsOngoing monitoring, patching, backups and a response plan on a monthly retainer.

Common questions

Which cloud should we use?

Usually the one your team or customers already use. We compare AWS and Azure on cost, services and skills before recommending.

Can you lower our cloud bill?

Often, through right-sizing, scheduling and removing idle resources. We show the savings estimate before we change anything.

Can you migrate without downtime?

We plan cutovers to keep downtime as short as possible, using staged traffic switching and a rollback plan. The right approach depends on your application.

Who responds when something breaks?

Under a managed plan, alerts reach our on-call engineer, and response times are written into the agreement.

Ready to review your cloud setup?

Tell us what you run today. We will come back with the risks, the savings and a plan.

Book a cloud review All services

RELATED SERVICES

DevOps AI & intelligent solutions Custom software IT support Data analytics

What we deliver

Ship more often, with fewer surprises.

We automate the path from commit to production and keep it healthy once it is live.

CI/CD pipelinesEvery commit is built, tested and deployed automatically, so releases become routine instead of events.

Containers with DockerApplications packaged once and run the same way on a laptop, in staging and in production.

Kubernetes and orchestrationScaling, self-healing and rolling updates for workloads that need them, without over-engineering the rest.

Safe release strategiesBlue-green and canary releases with one-click rollback, so a bad change is quick to reverse.

Automated testing gatesUnit, integration and end-to-end checks that must pass before anything reaches production.

Infrastructure as codeEnvironments defined in Terraform and Ansible, reviewed like code and rebuilt on demand.

DevSecOpsDependency and image scanning, secrets management and audit trails built into every pipeline.

Observability and incident responseLogs, metrics and traces with alerts, runbooks and on-call, plus reviews after every incident.

Delivery pipeline

One automated path to production.

Every change follows the same route, with checks at each stage and a feedback loop from live monitoring.

How it works

From manual releases to a reliable pipeline.

01AssessWe map how code reaches production today, where it slows or breaks, and the baseline to improve on.

02AutomateWe build pipelines, containers and infrastructure as code, starting with the slowest manual steps.

03HardenWe add test gates, security scans and rollback paths so speed does not cost stability.

04Operate and improveWe monitor, run on-call if needed and track delivery metrics so progress is visible.

Tools we use

Open, well-supported tooling.

CI/CD

GitHub ActionsGitLab CIJenkinsArgo CD

Containers

DockerDocker ComposeKubernetesHelm

Infrastructure as code

TerraformAnsibleCloudFormation

Quality

pytestJestPlaywrightSonarQube

Security

TrivySnykDependabotHashiCorp Vault

Observability

PrometheusGrafanaLokiSentryPagerDuty

Registries

Amazon ECRAzure Container RegistryGitHub Packages

Ways to work with us

Automate once or keep us on call.

Pipeline setupA scoped project to automate build, test and deploy for one application, with documentation and a handover.

DevOps retainerOngoing pipeline care, upgrades, on-call support and monthly delivery reports.

Team enablementWorkshops and pairing so your engineers can run and extend the platform themselves.

Common questions

Do we need Kubernetes?

Not always. Many products run well on simple container hosting. We recommend Kubernetes only when scale or complexity justifies the overhead.

Can you work with our existing repositories and tools?

Yes. We build on GitHub, GitLab or Bitbucket and on the tools your team already uses before suggesting anything new.

How do you measure improvement?

We track deployment frequency, lead time, change failure rate and time to restore, before and after the work.

How long does a first pipeline take?

It depends on your stack and tests. We give a time estimate after the assessment, before any work begins.

Ready to make releases routine?

Tell us how you deploy today. We will come back with the bottlenecks and a plan to fix them.

Book a DevOps review All services

RELATED SERVICES

Cloud infrastructure Custom software Web development IT support

What's included

01
Wireframes & prototypesFlows mapped first, then a clickable Figma prototype you can react to.
02
Design systemsReusable components, colours and type, so every new screen stays consistent and quick to build.
03
Usability testingShort sessions with real users to find what confuses them before launch.
04
Developer-ready handoffSpecs, assets and component notes organised so engineers build exactly what was designed.

Tools we use

DESIGN

FigmaFigJamFigma Variables

RESEARCH

User interviewsHotjarMicrosoft Clarity

PROTOTYPING

Figma PrototypeLottie

HANDOFF

Figma Dev ModeStorybook

ASSETS

SVGLucide iconsGoogle Fonts

What's included

01
Maintenance plansMonthly plans covering updates, bug fixes and small changes, with a named engineer and set response times.
02
Security reviewsAccess, backups and dependency checks, ending in a written list of risks ranked by urgency.
03
Technology roadmappingA 12-month plan for tools, hosting and AI opportunities, ranked by effort and return.
04
Day-to-day guidanceA senior engineer to ask before you buy a tool, sign with a vendor or start a build.

Tools we use

SUPPORT

JiraSlackGoogle WorkspaceMicrosoft 365

SECURITY

OWASP checklistsOWASP ZAPDependabotBitwarden

MONITORING

UptimeRobotSentryGrafana

BACKUP & RECOVERY

AWS BackupS3 versioningRestore drills

PLANNING

NotionMiro

What's included

01
AI agent developmentAgents that finish tier-1 work end to end inside your own tools, then pass edge cases to your team with the context attached.
02
AI chatbot developmentWebsite and WhatsApp chatbots that answer only from your approved content, qualify leads into your CRM and hand over to a person when unsure.
03
AI automationn8n and Python workflows that run approvals, follow-ups, reminders and reports across your apps, with every run logged.
04
AI voice agentsCalls answered at any hour in the languages you choose, with bookings written to your calendar or CRM and searchable transcripts.
05
Generative AI developmentRetrieval over your own documents, plus drafting, summarising and extraction tools, with guardrails and measured quality.
06
Data engineeringPipelines and quality checks that bring scattered data into one source, with Power BI and analytics views on top.
07
AI consultingA workflow and data audit, opportunities ranked by effort, risk and return, and a scoped first build you can approve or take elsewhere.

Tools we use

The full AI toolkit behind this service. We pick from it per project, based on your data, channels and budget.

Language models

OpenAI APIAnthropic Claude APIGoogle Gemini APIAzure OpenAIAWS BedrockLlama and Mistral (self-hosted)

Agents and orchestration

LangChainLangGraphLlamaIndexCrewAITool and function callingModel Context Protocol (MCP)

Chatbots and channels

WhatsApp Business APIWebsite chat widgetSlackMicrosoft TeamsEmailSMSTwilio

Voice AI

Twilio VoiceVapiElevenLabsDeepgramOpenAI WhisperGoogle Speech-to-Text

Generative AI and retrieval

Retrieval-augmented generation (RAG)Embeddings and vector searchpgvectorPineconeQdrantHugging FaceOCR and document parsing

Automation and integration

n8nPythonFastAPINode.jsREST APIs and webhooks

Data engineering

Apache AirflowdbtPandasPostgreSQLMongoDBRedisBigQuerySnowflakeGreat ExpectationsPower BIGoogle Sheets and Airtable

Evaluation and safety

Prompt and answer evaluationLangfuseLangSmithGuardrailsPII redactionHuman review queuesAudit logs

Business systems

ZendeskFreshdeskHubSpotZoho CRMSalesforceGoogle WorkspaceMicrosoft 365

Cloud and delivery

AWSAzureDockerCI/CDPrivate cloud deploymentMonitoring and logging

What we build

Single and multi-agent systemsOne agent per job, or several that hand work to each other and share context.

Tool and system accessAgents that read your CRM, helpdesk and databases and take approved actions.

Your keys, your hostingRun on your own model accounts and on cloud or private servers.

Guardrails and approvalsSpending limits, allowed actions and sign-off steps for anything risky.

Memory from your historyAgents learn from resolved tickets and corrections, with a human reviewing changes.

Monitoring and cost trackingResolution rate, answer quality and cost per task, visible to your team.

How it works

01Scope the jobWe map the workflow, the data and the finish line, and agree a baseline to beat.

02Build and testWe test against your real past cases until the agent meets the quality bar.

03Launch and tuneIt goes live in shadow mode first, then we monitor and improve it monthly.

Tech we use

OpenAIAnthropic ClaudeGoogle GeminiLangChainLangGraphCrewAIMCPPineconepgvectorRedisLangSmithPythonFastAPIPostgreSQLDockerAWS

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

What kinds of agents can you build?

Any workflow you can describe: support, lead follow-up, back-office, data checks or internal helpdesks.

Which models do you use?

We are model-agnostic and choose per job on accuracy, cost and speed. You can bring your own keys.

Who looks after the agent after launch?

We do, under a monthly plan covering monitoring, fixes and improvements.

Ready to scope your aI agent development?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI chatbot development AI automation AI voice agent Generative AI development Data engineering AI consulting

What we build

Website and WhatsApp botsOne chatbot brain across your site, WhatsApp, Slack and email.

Approved-content answersReplies come only from your documents, with the source shown.

Lead capture and scoringVisitors are qualified and pushed into your CRM with the conversation attached.

Smooth human hand-offWhen the bot is unsure, a person takes over with the full history.

Multilingual conversationsEnglish, Hindi and other languages, including mixed-language messages.

Chat analyticsSee top questions, gaps in your content and deflection rate each week.

How it works

01Collect your contentWe gather FAQs, policies and past chats and fix gaps and contradictions.

02Train and testWe replay real past conversations and review every wrong answer.

03Go live and learnWe launch on one channel, then expand as accuracy holds.

Tech we use

OpenAIAnthropic ClaudeGoogle GeminiRAGEmbeddingsWhatsApp Business APIWebsite chat widgetSlackSMSZendeskFreshdeskHubSpotZoho CRMNode.jsPostgreSQL

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Can the chatbot say things we have not approved?

It answers only from content you approve and hands over when the answer is not there.

Do we need a WhatsApp Business account?

Yes, and we handle the application and setup with you.

Can it connect to our CRM?

Yes. HubSpot, Zoho, Zendesk, Freshdesk and custom systems through APIs.

Ready to scope your aI chatbot development?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI automation AI voice agent Generative AI development Data engineering AI consulting

What we build

Workflow automationTriggers, branching and retries across your apps, built in n8n or Python.

Document and email handlingInvoices, forms and inboxes read, sorted and filed automatically.

Approvals and remindersRequests routed to the right person, with nudges until they are done.

Data entry and syncRecords kept consistent between your CRM, sheets and accounting tools.

Scheduled reportingWeekly and daily reports compiled and sent without anyone building them.

Run logs and alertsSee what ran, what failed and why, with alerts on errors.

How it works

01Map the processWe shadow the work and list every step, exception and owner.

02Automate the safe partWe start with the steps that rarely go wrong and keep review points in.

03Measure and extendWe track hours saved and add the next workflow once the first is stable.

Tech we use

n8nPythonFastAPINode.jsREST APIsWebhooksGoogle WorkspaceMicrosoft 365SlackHubSpotZohoAirtableOCROpenAIAnthropic ClaudePostgreSQLDocker

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Which tasks suit automation?

Rule-based, repeated tasks with clear inputs, such as data entry, routing, reminders and reporting.

What if a step fails?

It retries, then alerts a named person. Nothing fails silently.

Do we need new software?

Usually not. We connect the tools you already use.

Ready to scope your aI automation?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI chatbot development AI voice agent Generative AI development Data engineering AI consulting

What we build

Inbound call handlingCalls picked up at any hour, with no queue and no voicemail.

Booking and callbacksAppointments written straight into your calendar or CRM.

Outbound reminders and follow-upsConfirmation and follow-up calls that cut no-shows.

Natural, multilingual speechLow-latency voices in the languages your callers use.

Live transfer to a personWarm hand-over with a summary when a call needs a human.

Transcripts and summariesSearchable transcripts and a short summary after every call.

How it works

01Script the callsWe write the call flows from your real recordings and edge cases.

02Test with real callsWe run trial calls, tune the voice and fix awkward turns.

03Launch and reviewWe start with a share of calls, then review transcripts weekly.

Tech we use

Twilio VoiceVapiElevenLabsDeepgramOpenAI WhisperGoogle Speech-to-TextOpenAIAnthropic Clauden8nGoogle CalendarHubSpotZoho CRMPythonNode.jsAWS

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Can callers tell it is an AI?

We say it is an AI at the start of the call, and design it to be clear rather than clever.

Which languages are supported?

English and Hindi are common, and others are possible. We test each one with real callers.

Is call data kept private?

Recording and retention follow rules you set, and can run on your own cloud.

Ready to scope your aI voice agent?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI chatbot development AI automation Generative AI development Data engineering AI consulting

What we build

Document Q and AAsk questions over your contracts, manuals and reports, with sources shown.

Drafting and summarisingFirst drafts, summaries and reports in your house style.

Data extractionStructured fields pulled from PDFs, scans, emails and forms.

Internal knowledge assistantsOne place for staff to find policies, answers and past work.

Content and catalogue generationProduct copy and descriptions, reviewed before publishing.

Evaluation and guardrailsTest sets and checks so quality is measured, not assumed.

How it works

01Choose the use caseWe pick one task with a clear measure and gather the documents behind it.

02Build and evaluateWe build the retrieval, write the test set and compare model options.

03Release in stagesWe launch to a pilot group, collect feedback and widen access.

Tech we use

OpenAIAnthropic ClaudeGoogle GeminiLlamaMistralHugging FaceLlamaIndexLangChainRAGPineconeQdrantpgvectorOCRLangfusePythonFastAPIAWSAzure

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Will our data train public models?

No. We use settings and providers that keep your data out of training, or host models privately.

How do you reduce wrong answers?

Answers are grounded in your documents, cite sources and are tested against a set of known questions.

Can it work with scanned files?

Yes. We use OCR and document parsing, and flag low-confidence results.

Ready to scope your generative AI development?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI chatbot development AI automation AI voice agent Data engineering AI consulting

What we build

Connectors and ingestionData pulled from your apps, sheets, databases and APIs.

Warehouse and modellingClean, documented tables built for reporting and AI.

Pipeline orchestrationJobs scheduled, retried and monitored, with alerts on failure.

Data quality checksBad or missing data flagged before it reaches a dashboard.

Dashboards and analyticsPower BI views on top, refreshed on a schedule.

Data for AIClean, permissioned data prepared for search and model use.

How it works

01Audit your dataWe list sources, owners, gaps and the numbers people dispute.

02Build the pipelineWe build ingestion, cleaning and checks, then reconcile with known totals.

03Hand over and monitorWe document everything and keep watching freshness and quality.

Tech we use

Apache AirflowdbtPythonPandasSQLPostgreSQLMongoDBBigQuerySnowflakeRedisGreat ExpectationsPower BIGoogle SheetsAirtableDockerAWSAzure

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Where do we start?

With the report people trust least. Fixing that source usually fixes several others.

Can you work with our existing tools?

Yes. We connect to what you have before suggesting anything new.

How do you keep data accurate?

Automated checks run on every load and alert a named person on failures.

Ready to scope your data engineering?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI chatbot development AI automation AI voice agent Generative AI development AI consulting

What we build

AI readiness assessmentWe review your workflows, data and team to see what is ready now.

Opportunity rankingEach idea scored on effort, risk and projected return.

Data and tooling reviewWhat you have, what is missing and what to avoid buying.

Build, buy or skip adviceHonest guidance on vendors, custom builds and what not to do.

Roadmap and business caseA 12-month plan with costs and expected savings.

Pilot scopingA first build with success measures, ready to approve or hand to another team.

How it works

01DiscoverWe interview your team and watch the work to find where time goes.

02Assess and rankWe score the options and test the top ones against your data.

03Plan and decideYou get a written roadmap and a scoped pilot, with no obligation to build with us.

Tech we use

Process mappingData auditROI modellingRisk reviewVendor comparisonOpenAIAnthropic ClaudeGoogle Geminin8nPower BINotionMiro

Industries we work with

HealthcareSaaSFintecheCommerceeSportsGCCTravelHospitality

Common questions

Do we have to build with you afterwards?

No. The roadmap and pilot scope are yours to use anywhere.

How long does an assessment take?

Typically two to three weeks, depending on team size and how many workflows are in scope.

What do we need to prepare?

Access to a few people who do the work, and sample data or documents.

Ready to scope your AI roadmap?

Tell us the problem. We will come back with a plan, the expected return and a realistic timeline.

Book a call

OTHER AI SERVICES

AI agent development AI chatbot development AI automation AI voice agent Generative AI development Data engineering

2024Year founded

11+Engineers and specialists

20+Projects delivered

6Core service lines

Why Morris Infotech

A place to do your best work.

Real systems, real clientsYou work on AI agents, automation and software that clients use every day, not demos.

Senior people beside youA small team means direct feedback and code review from the engineers who ship.

Ownership from day oneYou own an outcome end to end, from scoping to support, with room to grow into it.

Learn AI by shippingWe test new models and tools on live work and share what we learn with the team.

Plain, honest communicationClear priorities, realistic deadlines and straight feedback in both directions.

Variety across the stackAI, web, mobile, cloud, data and marketing all sit under one roof.

Open roles

Find your role.

Do not see an exact match? Send us your CV anyway and tell us what you would like to build.

AI / Python EngineerBuild agents, RAG systems and APIs on LLM platforms.

EngineeringFull-time

Apply

n8n Automation DeveloperDesign workflows that connect CRMs, helpdesks and internal tools.

AutomationFull-time

Apply

Full-stack Web DeveloperShip fast, accessible web apps and dashboards for clients.

EngineeringFull-time

Apply

UI/UX DesignerTurn messy workflows into clear interfaces and design systems.

DesignFull-time

Apply

DevOps EngineerOwn deployment, monitoring and cost on AWS and Azure.

CloudFull-time

Apply

Digital Marketing ExecutiveRun Meta Ads and SEO programmes tied to measurable leads.

MarketingFull-time

Apply

How we hire

Four steps, no surprises.

01ApplySend your CV and a short note about work you are proud of.

02Intro callA relaxed conversation about your experience and what you want next.

03Practical taskA short exercise close to real project work, so you can show how you think.

04OfferA clear decision and, if it is a match, a clear offer.

Ready to join us?

Tell us about yourself and the work you want to do next.

Send your CV About our values

What's included

01
Data cleaning & pipelinesBring data from different sources together and keep it tidy.
02
KPI tracking & reportingAgree the metrics that matter, then report them consistently.
03
Predictive & trend analysisSpot patterns and likely next steps from your own history.
04
Decision-ready summariesPlain-language findings, not just charts.

What's included

01
Power BI dashboard buildsInteractive reports designed around the questions leadership asks.
02
Data source integrationConnect spreadsheets, databases and business apps into one model.
03
Scheduled refresh & alertsNumbers that update on their own, with alerts when they move.
04
Leadership-ready layoutsClear, uncluttered views that work in a meeting.

What's included

01
Search engine optimisationBe found for the searches your customers actually make.
02
Content & social strategyA realistic plan for what to publish, where and how often.
03
Landing pages that convertPages built with our web team to turn visits into enquiries.
04
Performance tracking & reportingSee what is working, and put effort where it pays.

What's included

01
Campaign strategy & setupClear goals, tracking and structure before any budget is spent.
02
Audience targeting & creativesThe right people, with ads designed to get a second look.
03
Lead-focused campaignsAds aimed at enquiries and sales, not vanity metrics.
04
Ongoing optimisation & reportingRegular tuning and plain reports on what your budget achieved.

Discover

We audit workflows, find the work AI can own and project the return.

Design

Agent behaviour, guardrails and screens, reviewed with you before build.

Build

Two-week sprints with a working demo each time.

Deploy

Integration, testing and a staged launch that protects daily operations.

Support

Monitoring, tuning and new capability as the business changes.

Discover

Workflow audit, data-readiness check and stakeholder interviews, ending in a written scope with cost, timeline and projected return before anything is built.

Design

We define what the system may and may not do, then prototype the flow in Figma so you can react before code is written.

Build

Each sprint ends in a live demo and a short call to review results on your real data and reprioritise.

Deploy

Staged rollout, evaluation on real cases, data migration and a rollback plan, timed around your busiest hours.

Support

Monitored uptime, a defined bug-fix response time and a monthly plan to improve accuracy and add capability.

It depends on complexity, so we scope it before you commit. As a guide, a focused web or mobile app takes 8-14 weeks; AI agents and automations vary with the data and integrations involved.

No. A data-readiness check is part of week one. We tell you what is usable now, what needs cleaning and what the first agent can realistically do.

We choose per project rather than from a fixed toolkit: LLMs with retrieval over your content, Python, n8n, Node.js, React and Flutter, hosted on AWS or Azure.

Every project includes a support window, and most clients move to a monthly plan covering monitoring, fixes and tuning as their data and needs change.

Yes. We work with clients remotely, wherever they are, and we can arrange in-person meetings when a project calls for it.

A small, named team from our in-house engineers — the same people from kickoff through to post-launch support, not a rotating group of juniors.

Still have a question?Ask us directly and we'll reply within one business day.

CALL+91 91838 37860

EMAILsales@morrisinfotech.com

HOURS24/7 available

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

Client: under NDA, regional freight and last-mile operator | Industry: Logistics | Fleet: ~420 vehicles, 3 depots | Timeline: ~7 months

At a glance

Metric	Result
Unplanned breakdowns	Down ~28%
Fuel cost per km	Down ~24%
Daily route planning	~3 hours to ~25 minutes
On-time delivery	86% to 94%

What was going wrong

The operator runs about 420 vehicles, from vans to tractor units, out of three depots, carrying contract freight and last-mile parcels. Nine dispatchers plan every day by hand. Growth was filling the diary, and it was also filling the repair bay.

Telemetry nobody read. Trackers from three vendors had been fitted over six years. Each had its own portal, its own export format and its own definition of idling. Data existed for every vehicle, yet people only opened the maps to ask where a truck was.

Maintenance was calendar-based, so it was wrong in both directions. Vehicles were serviced at fixed distances whether they had been worked hard or lightly, while a failing alternator still showed up as a roadside breakdown, a missed delivery window and a tow bill. The workshop lead reckoned about one breakdown in five gave warning in the data first. Nobody was looking.

Routes lived in a spreadsheet. Dispatchers knew their regions, but a morning's plan took around three hours and could not react to a closed road or a late loading dock. Fuel was the second-largest cost line, and nobody could say which routes, vehicles or habits were driving it.

The managing director put it plainly: "We have more data than ever and we decide the way we did in 2015."

What we built

One platform on top of the existing trackers: a clean telemetry layer, a maintenance risk model, a route planner, fuel analytics and an assistant for the dispatch desk. No new hardware.

Step 1: Unified telemetry layer

About eight weeks of integration, most of it normalisation. Three vendor APIs, fuel-card exports and the workshop's job-card system all feed one store. Every vehicle gets one internal ID, and idling, harsh braking and engine hours are defined once for the whole fleet.

One vendor's API dropped readings in tunnels and low-signal areas, so we built gap-filling and flagged low-confidence data instead of guessing. Around 30 trackers turned out to be installed wrongly or silent. Finding them was the first quick win.

Step 2: Predictive maintenance

Each vehicle is scored weekly for failure risk on battery, alternator, brakes and tyres. It is a gradient-boosted model trained on three years of job cards, not magic: strong on batteries and tyres, weaker on rare faults.

Every alert says why (for example, cranking voltage down 11% over six weeks), so the workshop lead can overrule it. Accepted alerts become a suggested booking in the next quiet slot.

Voltage and temperature trends
Fault codes and harsh-event counts
Mileage, load and route type
Past job-card history

Step 3: Route and load planning

The planner builds tomorrow's routes from orders, vehicle capacity, driver hours, loading windows and live traffic, and re-plans when something changes.

Dispatchers review, edit and approve. They know which customer shuts at 1 pm and which driver avoids the hill road in winter, so they enter those rules once and the planner remembers them.

Step 4: Fuel and driver insight

Fuel-card data is matched to distance and engine data per vehicle, and the report splits waste into routing, vehicle condition and driver behaviour. Two depots were idling for about 12% of engine hours.

Drivers get a weekly coaching score. Version one ignored heavy-load days and drivers rightly objected, so we normalised for load.

Step 5: Dispatcher assistant

A chat assistant answers questions such as which trucks are due a battery check this week, or why Route 14 overran, from live data with the source shown. It cannot dispatch or book anything on its own.

How we rolled it out

Months 1-2: Integration and clean-up. Vendor APIs, vehicle mapping and the 30 dead trackers.

Months 3-4: Fuel analytics first. No AI needed, only correct data and correct maths. The idling finding won the team over.

Month 5: Maintenance model in shadow mode. Six weeks of silent scoring, compared with what actually broke. Too many low-value tyre alerts, so we raised the threshold.

Month 6: Route planner. One depot first, then all three.

Month 7: Assistant and handover. Tuning, training and a monthly review plan.

Results

After four months of full use, unplanned breakdowns were down about 28% and fuel per km about 24%. Part of that is seasonal, so we compared like-for-like months. Planning time fell to roughly 25 minutes. No dispatch roles were cut: the team now spends its time on exceptions and customer calls.

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

Client: under NDA, multi-site clinic and diagnostics group | Industry: Healthcare | Sites: 9 clinics, ~140 staff | Timeline: ~6 months

At a glance

Metric	Result
Missed calls at peak hours	~35% to under 5%
Appointment no-shows	~22% to ~13%
Front-desk time per booking	~6 min to ~1.5 min
Patient data leaving group servers	None

What was going wrong

The group runs nine clinics and a diagnostics lab with about 140 staff. Each site booked patients its own way: phone, a front-desk WhatsApp on a personal handset, a walk-in register, and two different appointment tools.

Missed calls meant missed bookings. Between 9 and 11 am, the front desk was checking patients in while the phone rang. Roughly one call in three went unanswered, and those callers rarely rang back.

No-shows were expensive. Reminders were sent by hand when someone remembered. Doctors and scan rooms sat idle in slots that could have been filled.

Patients arrived unprepared. Paper intake forms were retyped, with errors in names and dates of birth. Preparation questions, such as fasting before a blood test or medicines to pause, were not always asked, so tests were rescheduled.

Privacy was non-negotiable. Leadership refused to send patient details to a public chatbot service. Any solution had to run on infrastructure the group controlled.

What we built

One scheduling layer, one conversational agent, automatic reminders and digital intake, all deployed privately. The agent books and prepares patients. It never gives medical advice.

Step 1: One scheduling layer

We connected both appointment tools, doctor rosters and room and equipment calendars into a single availability service. The hard part was identity: one doctor appears under three spellings across sites, and some work at several clinics. We built a master record for every clinician and room.

Step 2: The booking agent

Patients message on WhatsApp or the website in English or Hindi. The agent books, reschedules and cancels, and asks the right preparation questions for each test type. If a message describes anything urgent, it stops and hands over to the front desk immediately.

No diagnosis, no interpretation of results
Confident answers are sent, unsure ones go to staff for review
Answers come only from approved clinic content
Every conversation is logged for audit

Step 3: Reminders and waitlist

Reminders go out at set intervals with a one-tap reschedule. When a slot frees up, the next person on the waitlist is offered it automatically. This did more for utilisation than any other single feature.

Step 4: Digital intake

Patients complete intake before arrival. Answers are stored in structured form, and a nurse reviews any flagged item, such as medication or allergy, before the visit.

Step 5: Private deployment

Everything runs on the group's private cloud, with a model hosted in-region, role-based access and retention rules set by their compliance lead. A self-hosted model is less capable than the largest public ones, so we kept the agent's scope narrow and grounded it in the clinics' own content.

How we rolled it out

Month 1: Discovery with the front desk. We shadowed two sites and wrote down the real booking rules, including the unwritten ones.

Months 2-3: Scheduling layer. Both systems, all rosters, one availability view.

Month 4: Shadow mode at two clinics. Staff saw the agent's drafts before patients did. It offered the earliest slot even when a patient needed one specific doctor, and it stumbled on mixed Hindi-English messages. Both fixed.

Month 5: Live rollout. Two clinics, then all nine.

Month 6: Reminders, waitlist and tuning. Plus staff training and a monthly accuracy review.

Results

Within three months of full rollout, peak-hour missed calls fell below 5%, no-shows dropped to about 13% and a booking took the front desk roughly a minute and a half. Front-desk staff now handle complex cases and in-person patients, rather than the phone queue.

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
of routine tickets resolved without a human	72%

The client

An online retailer handling a high volume of order, delivery and refund queries across email, chat and social channels.

The challenge

As order volume grew, so did the queue of repeat questions: where is my parcel, can I change my address, how do I return this. Help-centre articles existed, yet customers still wrote in, replies slowed, and agents spent most of the day on work that followed a few patterns. Generic helpdesk AI had been tried and gave confident but wrong answers.

Most tickets were routine order questions answered by hand
Slow replies hurt satisfaction and repeat sales
Customer data had to stay inside the company's own systems
Agents were burning out on repetitive work

Project goals

Resolve routine order and refund requests automatically
Answer only from live order data and approved policy, never guess
Hand over to a person, with full context, when a case needs judgement
Give managers clear reporting on what customers ask about

Our solution

We built an AI support agent that sits on top of the retailer's helpdesk and order systems. It reads the question, looks up the real order, and either answers, takes a permitted action or escalates. Every answer is grounded in live data and written policy, which removes the guesswork that made earlier tools unreliable.

How it works

Classify each incoming message by intent and urgency
Look up the order, shipment and policy details needed
Answer, or perform an allowed action such as a standard refund
Escalate edge cases to a person with the conversation summarised
Tag the ticket and feed topic trends into weekly reporting

How we delivered

Discover. We reviewed past tickets to find the intents worth automating, wrote the rules for each, and agreed what the agent may and may not do alone.

Build. We connected the helpdesk, order system and policy content, then tested the agent against real historical tickets.

Launch & tune. The agent went live on a small share of traffic first. We widened its scope as accuracy held and reviewed escalations every week.

Results

72% of routine tickets resolved without a human.

Routine order questions are handled without waiting for an agent
Human agents focus on complex and sensitive cases
Customers get an answer at any hour
Managers see ticket topics and trends without manual tagging

Built with

LLM · retrieval over help-centre content · helpdesk and order-system integrations · n8n workflows

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
faster reporting cycle	5×

The client

A marketing agency managing campaigns for many clients across several ad platforms.

The challenge

Every week analysts exported numbers from each platform, rebuilt the same reports by hand and then debated what to change. By the time budgets moved, the data was already out of date, and creative decisions leaned on opinion.

Performance data split across platforms and spreadsheets
Reporting consumed analyst time every week
Budget shifts happened late
No consistent way to judge which creatives worked

Project goals

One consolidated view of every account
Automated creative performance analysis
Budget suggestions backed by data
Client-ready reports without manual assembly

Our solution

We unified ad-platform data into a single model and added an AI layer that scores creatives, spots fatigue and proposes budget moves for each account. A weekly summary is generated per client, which analysts review and send.

How it works

Pull campaign data from each ad platform automatically
Normalise metrics so accounts can be compared
Score creatives and flag what to pause, test or scale
Propose budget reallocation for each account
Generate a weekly summary for analyst review

How we delivered

Discover. We mapped the agency's reporting routine and agreed which metrics and decisions to automate first.

Build. We built the data connections, scoring logic and summary generator, and checked outputs against analysts' own reports.

Launch & tune. A few accounts ran in parallel with manual reporting until the team trusted the output, then the rest moved over.

Results

5× faster reporting cycle.

Weekly reporting no longer needs manual assembly
Analysts spend their time on strategy
Budget decisions use current data
Clients receive consistent, clear summaries

Built with

Ad-platform APIs · data warehouse · LLM summaries · Power BI dashboards

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
less manual review time	80%

The client

A cross-border payments firm that must track regulation in several regions.

The challenge

Rules changed constantly and were published in different formats by many bodies. A small compliance team read every update to decide what mattered, which was slow and risked missing the one change that did.

Many regulator sources in different formats
Most updates were not relevant to the firm
Impact assessments started from a blank page
Evidence of review was kept by hand

Project goals

Watch every relevant source continuously
Surface only the changes that affect the firm
Draft a first-pass impact assessment
Keep a complete audit trail

Our solution

We built a monitoring agent that ingests regulator feeds, classifies each change by relevance to the firm's products and regions, and drafts an impact note. A person always reviews and approves, and every step is logged.

How it works

Collect updates from regulator feeds and publications
Extract and classify each change by topic and region
Rank relevance against the firm's products and obligations
Draft an impact assessment with links to the source text
Route to a reviewer and record the decision

How we delivered

Discover. We listed the sources and obligations that matter and defined what a relevant change looks like.

Build. We built ingestion, classification and drafting, tested against past changes the team had already assessed.

Launch & tune. Reviewers worked alongside the agent first, and their feedback sharpened the ranking before it became the default workflow.

Results

80% less manual review time.

Compliance staff read what matters instead of everything
Impact assessments start from a draft
Every decision has an audit record
New sources can be added without a rebuild

Built with

Document ingestion · LLM classification and summarisation · retrieval · review workflow

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
average revenue uplift	14%

The client

A property operator pricing units across several cities.

The challenge

Rents were set by hand from a handful of comparable listings and revisited rarely. Prices drifted from the market, so some units sat empty while others were let for less than they could earn.

Pricing relied on limited manual comparisons
Rents were reviewed infrequently
No consistent method across cities
Prices were hard to explain to owners

Project goals

Price every unit from current market signals
Keep the operator in control with clear rules
Refresh recommendations regularly
Show the reasoning behind each number

Our solution

We built a pricing engine that combines local market signals with each unit's own history and features, then recommends a rent within guardrails the operator sets. Recommendations refresh daily and each comes with the factors behind it.

How it works

Collect market and listing data for each area
Join it with unit attributes and lease history
Estimate the best rent and expected time to let
Apply the operator's minimums, caps and rules
Publish the recommendation with its reasoning

How we delivered

Discover. We agreed the pricing rules and which signals were available and trustworthy.

Build. We built the data pipelines and pricing model, and back-tested recommendations against past leases.

Launch & tune. Recommendations ran in advisory mode first, with managers approving each change until confidence grew.

Results

14% average revenue uplift.

Pricing follows the market, not memory
Managers can explain every recommendation
Guardrails keep decisions inside policy
One method works across all cities

Built with

Market data ingestion · pricing model · scheduled pipelines · pricing dashboard

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
faster vendor shortlisting	10×

The client

A procurement team that reviews long vendor proposals for large purchases.

The challenge

Each RFP produced hundreds of pages from several vendors. Reading, extracting answers and scoring by hand took weeks, and scoring varied from one reviewer to the next.

Very long proposals in inconsistent formats
Hand scoring varied from person to person
Weeks passed before a shortlist existed
Hard to trace a score back to evidence

Project goals

Read every proposal into a common format
Score against weighted, agreed criteria
Rank vendors consistently
Link each score to its source text

Our solution

We built an evaluation platform that ingests proposals, extracts the answer to each requirement and scores it against criteria and weights set by the team. Every score links back to the passage it came from, so reviewers can check and adjust.

How it works

Ingest proposals in common document formats
Split them into sections and map to requirements
Extract each vendor's answer to every requirement
Score and rank using the team's weighted criteria
Let reviewers inspect evidence and override scores

How we delivered

Discover. We captured the criteria, weights and past decisions the team used.

Build. We built parsing, extraction and scoring, and compared results with a past, already-decided RFP.

Launch & tune. The platform ran alongside a live RFP, then became the first pass for later ones.

Results

10× faster vendor shortlisting.

Proposals are scored consistently
Shortlists arrive far sooner
Every score is traceable to evidence
Reviewers keep the final decision

Built with

Document parsing · LLM extraction · retrieval · scoring engine · review interface

Representative engagement. Client details are withheld, and the figures are illustrative until replaced with verified results.

At a glance

Metric	Result
less food waste	26%

The client

A multi-location food and beverage business with years of unused sales data.

The challenge

Point-of-sale systems recorded every sale, but the data was never joined with waste or labour. Ordering, staffing and menu choices leaned on instinct and local habit.

Sales, waste and labour data lived apart
Ordering and prep were guesswork
Low-margin items went unnoticed
Managers lacked a single daily view

Project goals

Join sales, waste and labour data
Forecast demand by location
Spot menu items that hurt margin
Give managers one clear daily view

Our solution

We cleaned and joined the data in one warehouse, built demand forecasts per location and item, and added a daily view with recommendations for ordering, prep and staffing.

How it works

Extract data from point-of-sale and operations systems
Clean and join sales, waste and labour records
Forecast demand by location, day and item
Highlight margin and waste issues by menu item
Deliver a daily view to each manager

How we delivered

Discover. We inventoried data sources and agreed the decisions managers make every day.

Build. We built the pipeline, forecasts and dashboards, checking forecasts against past weeks.

Launch & tune. One location piloted the daily view, and we refined it with managers before rolling out to the rest.

Results

26% less food waste.

Ordering and prep follow forecasts
Waste is visible by item and location
Menu decisions consider margin
Managers start the day with one clear view

Built with

Data pipeline · forecasting models · cloud data warehouse · Power BI dashboards

Workflows an agent can own

Where Healthcare teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Patient intake and schedulingCollects details on WhatsApp or web, books the right slot and sends reminders.

Enquiry routingSends each request to the right department using your rules, without giving medical advice.

Records and documentsReads referrals, reports and forms, then files the key fields into your system.

Billing and insurance questionsAnswers coverage and invoice queries and flags claims that need a person.

Follow-ups and recallsSends check-up and post-visit reminders using wording you have approved.

Staff knowledge assistantAnswers policy and procedure questions from your own documents, with sources.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real clinic and admin task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to clinic systems, calendars and WhatsApp, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Privacy by designPersonal data is minimised and redacted, and hosting can sit in a private cloud to match your policy.

Systems we connect

Built around the tools you already use.

Channels

WhatsApp Business APIWebsite chatSMSEmail

Systems

PostgreSQLn8nREST APIsPrivate cloud

Common questions

Does the agent give medical advice?

No. It handles scheduling, information and routing, and hands clinical questions to your staff.

Can data stay in our own cloud?

Yes. We can deploy in a private cloud and redact personal data, based on your policy.

Ready to put an agent to work in Healthcare?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your Healthcare project All services

RELATED WORK AND SERVICES

Patient intake case study AI chatbot development AI automation

OTHER INDUSTRIES

SaaS Fintech eCommerce eSports GCC Travel Hospitality

Workflows an agent can own

Where SaaS teams save the most time.

Most clients start with one of these, prove the return, then add the next.

In-app support agentAnswers product questions from docs and tickets, with sources, and escalates with full context.

Onboarding guideWalks new users through setup and nudges stalled accounts at the right moment.

Ticket triageTags, prioritises and routes tickets, and drafts replies for agents to approve.

Churn and health signalsCombines usage and billing data to flag at-risk accounts for success managers.

Trial and lead qualificationResearches inbound leads, scores fit and books demos in your CRM.

Release notes and docsDrafts changelogs and help articles from tickets and shipped work for review.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real product and support task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your product, help centre, CRM and Slack, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Answers you can trustReplies come from your docs and tickets with sources, and are tested on real questions before launch.

Systems we connect

Built around the tools you already use.

AI

OpenAIClaudeLangChainpgvector

Business systems

HubSpotSalesforceZendeskSlack

Common questions

Can the agent live inside our product?

Yes. We can embed it through an API or widget, or run it in your help centre and Slack.

How do you keep answers accurate?

We ground answers in your own content, cite sources and test against real customer questions before launch.

Ready to put an agent to work in SaaS?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your SaaS project All services

RELATED WORK AND SERVICES

AI agent development Generative AI development

OTHER INDUSTRIES

Healthcare Fintech eCommerce eSports GCC Travel Hospitality

Workflows an agent can own

Where Fintech teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Onboarding and KYC checksReads identity and business documents, extracts fields and flags gaps for a reviewer.

Regulatory change monitoringTracks regulator updates, summarises the impact and routes actions to owners.

Disputes and case handlingGathers evidence, drafts case notes and prioritises disputes for analysts.

Support with guardrailsAnswers account and product questions and never moves money without approval.

Credit and risk summariesCompiles applicant data into a structured summary for underwriters.

Reconciliation and reportingMatches records across systems and prepares exception reports.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real compliance and operations task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your core systems, document stores and review queues, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Decisions you can defendEvery output keeps its sources and reasoning, so reviewers and auditors can trace it.

Systems we connect

Built around the tools you already use.

Payments and data

StripeRazorpayPostgreSQLApache Airflow

AI and reporting

OpenAIClaudePythonPower BI

Common questions

Can the agent approve or reject applications?

We design it to prepare and recommend, with your reviewers making the final call.

Where is our data stored?

In your cloud account or a private deployment, with access controls and logging agreed with your security team.

Ready to put an agent to work in Fintech?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your Fintech project All services

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Workflows an agent can own

Where eCommerce teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Order status and returnsLooks up orders, explains policies and starts returns within your rules.

Product adviceRecommends items from your catalogue based on needs, size and stock.

One inbox across channelsHandles WhatsApp, email and chat together and escalates with context.

Abandoned cart recoveryFollows up with timely, relevant messages instead of generic blasts.

Catalogue upkeepDrafts descriptions, tags and translations for your team to review.

Stock and demand alertsFlags stock-outs and demand shifts before they cost sales.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real support and operations task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your store, helpdesk, order system and WhatsApp, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Limits you setRefunds, discounts and exceptions stay inside rules you define, and larger cases go to your team.

Systems we connect

Built around the tools you already use.

Commerce

ShopifyWooCommerceStripeRazorpay

Support and channels

ZendeskFreshdeskWhatsApp Business APIn8n

Common questions

Does it work with our store platform?

We connect to Shopify, WooCommerce and custom stores through their APIs.

Can it process refunds on its own?

Only within limits you set. Larger or unusual cases go to your team.

Ready to put an agent to work in eCommerce?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your eCommerce project All services

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Workflows an agent can own

Where eSports teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Community moderationFlags abuse and spam in chat and Discord, and escalates edge cases to moderators.

Player and fan supportAnswers questions about tickets, rewards, accounts and rules.

Tournament operationsHandles registration, check-ins, brackets and match reminders.

Content repurposingTurns streams and matches into highlights, summaries and posts for review.

Sponsor reportingPulls reach and engagement data into sponsor-ready reports.

Scouting and performance insightsSummarises match data into player and team reports.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real community and events task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to Discord, Slack, ticketing and your data feeds, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Moderation with reviewContent is flagged and held for moderators, using rules your community team sets.

Systems we connect

Built around the tools you already use.

Community

DiscordSlackWhatsApp Business APIEmail

Data and AI

PythonPostgreSQLPower BIOpenAI

Common questions

Can it moderate live chat?

It can flag and hold content for moderator review, using rules your community team sets.

Do we need game data to start?

No. Support and operations agents work without it, and match insights use whatever data feeds you have.

Ready to put an agent to work in eSports?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your eSports project All services

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Workflows an agent can own

Where GCC teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Bilingual supportAnswers in Arabic and English across WhatsApp, web and voice with a consistent tone.

Licensing and paperworkPrepares and checks documents, tracks renewals and flags expiries.

Tender and proposal responseReads RFPs, drafts answers from past bids and scores fit.

Document processingExtracts data from invoices, contracts and IDs in both languages.

HR and staff requestsHandles leave, letters and policy questions for large, multinational teams.

Executive reportingTurns operational data into weekly dashboards and summaries.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real operations and customer task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your ERP, document stores, WhatsApp and voice channels, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Data residency optionsWe can host in cloud regions you choose, or in a private deployment, to meet your rules.

Systems we connect

Built around the tools you already use.

Channels

WhatsApp Business APIVoice AIWebsite chatEmail

Platform

AWSAzurePostgreSQLn8n

Common questions

Do you support Arabic?

Yes. We build and test agents in Arabic and English, including mixed-language conversations, on your own examples.

Can data stay in the region?

We can host in the cloud regions you choose, or privately, to meet your data residency requirements.

Ready to put an agent to work in GCC?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your GCC project All services

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Workflows an agent can own

Where Travel teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Trip planning and quotingBuilds itineraries and quotes from supplier availability and your pricing rules.

Changes and cancellationsHandles amendments within fare rules and escalates complex cases.

Disruption handlingSpots delays and cancellations and offers options to affected travellers.

Multilingual supportAnswers visa, baggage and booking questions in the traveller's language.

Supplier and fare monitoringTracks price changes and availability across suppliers.

Post-trip follow-upCollects feedback, issues documents and invites repeat bookings.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real sales and support task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your booking engine, supplier APIs and WhatsApp, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Approvals built inBookings and changes run within limits and approvals you define, with exceptions sent to your team.

Systems we connect

Built around the tools you already use.

Channels

WhatsApp Business APIVoice AIWebsite chatEmail

Systems

StripeRazorpayPostgreSQLn8n

Common questions

Can the agent make real bookings?

Yes, through your booking engine or supplier APIs, within limits and approvals you define.

How does it handle disruptions?

It monitors trip status, tells travellers early and offers options your team has pre-approved, escalating the rest.

Ready to put an agent to work in Travel?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your Travel project All services

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Workflows an agent can own

Where Hospitality teams save the most time.

Most clients start with one of these, prove the return, then add the next.

Reservations and enquiriesAnswers availability and rate questions and books rooms or tables on WhatsApp and web.

Guest conciergeHandles requests, recommendations and in-stay questions in the guest's language.

Housekeeping and maintenanceTurns guest requests into tasks and routes them to the right team.

Review responsesDrafts on-brand replies to reviews and flags urgent issues.

Menu, stock and waste analyticsForecasts demand and highlights waste so you can cut costs.

Revenue and pricing supportSuggests rate changes from demand, events and occupancy.

How it works

From one workflow to a working agent.

01Map the workflowWe follow a real front-of-house and operations task from start to finish and pick the one that costs your team the most time.

02Build the agentWe connect it to your PMS, POS, WhatsApp and review sites, with rules and approvals that match how you work.

03Pilot with reviewThe agent runs beside your people, with humans approving until accuracy is proven on your own data.

04Run and improveWe watch answers, cost and exceptions each month, then widen what the agent owns.

Control and safety

You stay in charge.

Human in the loopYour people approve sensitive steps, and unclear cases are handed over with full context.

Full audit trailEvery action and answer is logged, so you can review what the agent did and why.

Your voice, your rulesTone, language and escalation rules are set with your team and tested before launch.

Systems we connect

Built around the tools you already use.

Guest channels

WhatsApp Business APIWebsite chatVoice AIEmail

Systems

PMS and POS APIsPower BIPostgreSQLn8n

Common questions

Does it connect to our PMS or POS?

We integrate through their APIs where available, and use n8n workflows for systems with limited access.

Will it sound like our brand?

Yes. We set tone, language and escalation rules with your team and test them before launch.

Ready to put an agent to work in Hospitality?

Tell us the workflow that costs you the most time. We will come back with a plan, the expected return and a realistic timeline.

Discuss your Hospitality project All services

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We Build AI That Turns Ideas Into Reality.

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Every industry has workflows an agent can own.

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Built for production, not for demos.

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Senior engineers building AI and cloud systems that hold up in production.

A small, senior studio that builds AI-first software.

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AI & intelligent solutions

Cloud infrastructure

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Every industry has workflows an agent can own.

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