AI and automation · Specialism 03 of 04

Chatbots and AI Agents

Assistants that answer from your data and know their limits.

We build chatbots and AI agents that answer from your own data, take safe actions through your systems, and hand off to a person when they reach the edge of what they should do.

Related
AI integration, Workflow automation, Predictive analytics
Cadence
Two-week shipping rhythm
Team
Expert engineers and designers
Source code
Yours from commit one

Trusted by city corporations, retailers and founders across the Gulf, Europe, Bangladesh and beyond.

Verified onClutch
Al Tawash Al Maliky TailoringThe Flutter WayDhaka North City CorporationAl Ataar Al Maliky TailoringNaqsha Mens TailoringSpecial TailoringDhaka South City CorporationAl Ataar Golden Tailoring & Trading974 TailoringTelehawks SolutionsAlgonize
A deeper look

Everything to know about chatbots and agents.

Algoramming builds chatbots and AI agents for teams across the UAE, Qatar, Saudi Arabia, the US, the UK, and Australia. We create assistants that answer from your own content through retrieval (RAG), take safe actions through your systems, and hand off to a human when they should, so they help customers rather than embarrass the brand.

Written for the people buying the product and for the people who will run it after launch.

01

RAG-grounded first, clever second

A chatbot that improvises answers is a liability. We ground assistants in your actual content, your documentation, policies, and product data, so their answers trace back to something true. When a question falls outside what they know, they say so and hand off rather than inventing a confident guess. That restraint is exactly what makes an assistant safe to put in front of customers, and it is the part most rushed builds skip.

02

From answering to acting, carefully

The real value often comes when an assistant can do something, check an order, book a slot, update a record, not just talk about it. We connect agents to your systems through well-defined, permissioned tools, so their actions are constrained to what they are allowed to do and logged for accountability. Higher-risk actions sit behind confirmation or human approval. The result is genuinely useful, without handing an unpredictable model the keys.

Outcomes

Outcomes, not deliverables.

Success is measured in shipped value you can use, in two-week increments.

Two-week shipping rhythm
  1. 01

    An assistant that answers accurately from your content

  2. 02

    Deflection of routine questions, freeing your team

  3. 03

    Safe, permissioned actions rather than a chat-only toy

  4. 04

    A clean handoff to a human when it matters

What we deliver

Concrete artifacts, not slide decks.

Everything lands in your repositories, your cloud and your control.

  • A chatbot or agent grounded in your knowledge base
  • Safe tool and system integrations for real actions
  • Guardrails, fallback, and human handoff
  • Analytics on questions, deflection, and gaps
Process

The same expert team, the same playbook.

The first release is scoped to the smallest version that proves its worth. Everything after that is a measured increment.

01Phase 01 · 1 to 2 weeks

Discover

We pin down the use case, the data available, and the cost of getting an answer wrong before building anything.

02Phase 02 · 1 to 2 weeks

Design

We design the retrieval, prompts, guardrails, and the human-in-the-loop points that match the risk.

03Phase 03 · two-week sprints

Build

We integrate the feature or automation into your product and stand up an evaluation harness alongside it.

04Phase 04 · 1 week

Launch

We ship behind flags, watch quality, cost, and latency on real traffic, and tune before widening.

05Phase 05 · ongoing

Support

We monitor accuracy as the world drifts, retrain or re-prompt as needed, and keep the guardrails honest.

Selected work

Software we are proud to put our name on.

Sparrow: A Serverless, Peer-to-Peer Photo and Video Sharing App
Photography · Social · Consumer App · Privacy · Real-time Communication · WebRTC · Mobile · 2026

Sparrow: A Serverless, Peer-to-Peer Photo and Video Sharing App

Sparrow is a serverless, peer-to-peer photo and video sharing app built by Algoramming. Your phone becomes a live host and the people you invite connect directly, so photos and videos stream device to device over encrypted WebRTC, never uploaded, never stored in the cloud.

0 Files uploaded to a server1,000+ Photos per sessionAndroid & iOS Platforms
Read the case study
From Storefront to Doorstep: How Algonize Gives Multi-Branch Businesses One Real-Time Command Center
Retail · E-commerce · Restaurants · Food Service · SME · SaaS · ERP · CRM · Delivery · 2026

From Storefront to Doorstep: How Algonize Gives Multi-Branch Businesses One Real-Time Command Center

Algonize is the cloud ERP, CRM and POS platform built in Dhaka for multi-branch retail shops, restaurants and delivery businesses. This case study shows how one real-time dashboard unifies sales, inventory, riders, loyalty and accounting across Android, iOS, macOS and the web.

3 Client apps6 Platforms8 Payment methods
Read the case study
From clients

Hear it from the people who run the software.

“We’re happy with the DSCC Waste Management System developed by their team. It has made our daily operations, data tracking, and reporting much easier to manage. The team was professional throughout the project, and their ongoing support has been really helpful whenever we needed assistance. Overall, a great experience working with them.”
Md. Sufi Ullah Siddik BhuiyanProject Director, Matuail Sanitary Landfill Development & Extension Project, DSCC
“We’ve been using their DNCC Vehicle Equipment Management System for almost a year, and it has made managing our equipment and stock records much easier. The team is professional, friendly, and always helpful whenever we need support. Overall, it’s been a really good experience working with them.”
Abul Hasnat Md. Ashraful AlamChief Executive Engineer, DNCC
“I've been using this CRM software for the last 2 years and it has truly transformed how we handle our operations. This software is a game-changer in terms of efficiency and functionality. A top-notch software solution that has exceeded our expectations. Really appreciate themselves. The after-service of their product is just outstanding.”
Iftekhar Hossain MunnaFounder, Al Tawash Al Maliky Tailoring
Why teams stay with us

A partner you can trust with the whole thing.

No sales layer, no junior swap-ins, no surprise invoices. This is what every client gets, in writing, before work starts.

01

Experienced people on the work

The engineer who scopes your project reviews every line that ships. Nobody is swapped out for a junior after the kickoff.

02

Costed before we build

A one-to-two-week discovery ends in an itemised plan. After that, two-week sprints, each with a recorded demo and a changelog you can forward to your board.

03

You own everything

Source code, infrastructure, domains and secrets live in your accounts from day one. A walk-away clause is written into every contract.

04

We stay after launch

Monitoring, incident response and small improvements, with a named human who answers. Urgent tickets under a maintenance contract are handled around the clock.

Ways to work together

Three shapes, one playbook.

Every engagement starts with a short discovery that ends in a costed, itemised plan. No rate-card surprises, no minimum-month lock-in.

Fixed scope · Fixed price

Project

Discovery through launch and handover, for one agreed price and date.

Best when the brief is clear and the deadline is firm.

Monthly · Fixed expert allocation

Retainer

A rolling backlog we re-rank together, with the same experienced people every month.

Best when priorities change faster than annual planning.

Per engineer · Monthly

Embedded

Our engineers join your Slack, repos and sprint board as part of your team.

Best when your in-house engineers need expert support.

Stack and toolkit

Pragmatic tools. Expert judgement.

Well-supported tools your future hires already know, chosen for the years of maintenance after launch.

Models
OpenAIAnthropicOpen-weight modelsEmbeddings
Application
PythonTypeScriptLangChainFastAPI
Data and retrieval
PostgreSQLpgvectorRedisPipelines
Quality and delivery
Evaluation setsGuardrailsDockerObservability
Industries we ship for
FintechSaaSE-commerceRetail and POSPublic sectorCRMERPEdTechHealthcareLogisticsReal estateMedia
FAQ

Things teams ask before signing.

Something else on your mind? Email us and a lead engineer answers within one business day.

How do you build a chatbot grounded in our own data?

We use retrieval-augmented generation (RAG): your documentation, policies, and product data are indexed, and the assistant retrieves the relevant passages before it answers, so its replies trace back to your real content rather than the model's general training.

How do you stop the chatbot from hallucinating?

By grounding it in your content through retrieval, constraining it with guardrails, and having it defer to a human when it is unsure rather than guess. We also monitor real conversations to find and close gaps, and are honest that this reduces confident errors sharply without removing them entirely.

Can the agent take real actions, not just answer questions?

Yes. With safe, permissioned integrations an agent can take real actions in your systems, checking an order, booking a slot, updating a record, with higher-risk steps gated behind confirmation or human approval and every action logged.

Where can we deploy it?

On your website, in your product, or inside tools like your support desk or messaging channels, wherever your users already are.

Do we own the source code?

Yes. Source, infrastructure configuration and documentation are pushed to your repositories from day one, and the cloud accounts stay in your name. If we part ways, you keep everything and nothing stops working.

How do you price a project?

On scope. A one-to-two-week discovery produces an itemised estimate for a defined first release, so you see the full cost before committing to the build.

How long does a first version take?

A focused v1 usually takes three to six months, shipped in two-week increments you can test as they land. A clickable prototype typically exists within fourteen days of the brief.

Can you work in our timezone?

Yes. Our team works on GMT+6, with at least six hours of daily overlap with the Gulf, Europe, the UK, the US and Australia, and demos are recorded for anyone who missed the call.

What happens after launch?

We keep watching the metrics, respond to incidents and ship small improvements under a maintenance agreement, for as long as you want us. Runbooks and monitoring are in place from day one, so nothing depends on memory.

Explore the rest of AI and automation

The discipline, and its other specialisms.

Go deeper on chatbots and agents
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Claude Haiku 5.5 vs GPT-6 Luna

We compare Claude Haiku 5.5 vs GPT-6 Luna, analyzing their pricing curves, tokenizer taxes, and agentic benchmarks. Learn how to optimize your cloud costs.

ClaudeOpenAIAI agents
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Next move

Send the brief. We will take it from there.

Reply within one business day, NDA on request, and a free 30-minute discovery call before anything is priced.

ReplyWithin 1 business day
DiscoveryFree 30-min call
EngagementFixed scope or retainer
Overlap6+ hours, any region

support@algoramming.com · GMT+6