AI chatbots and assistants that answer from your own data
Generic chatbots guess. We build retrieval-augmented generation (RAG) assistants that answer from your documents, help-desk articles and databases — and show the source behind every answer. Practical AI that saves your team hours each week.
What you get
- Answers grounded in your own sources
- Private data stays private
- Works with OpenAI, Claude or open models
- Measurable time saved per week
Our ai & chatbot development services
Customer support chatbots
Answer common questions 24/7 on your website or WhatsApp and hand off to a human when needed.
RAG knowledge assistants
Search across PDFs, wikis and internal docs in plain English, with citations for every answer.
LLM integration into your product
Add summarization, drafting, classification or semantic search to the software you already run.
AI agents & workflow automation
Agents that read emails, fill forms, update records and trigger actions across your tools.
Document processing
Extract structured data from invoices, contracts and forms automatically and accurately.
AI strategy & proof of concept
A short, fixed-scope pilot to prove value on your data before you commit to a full build.
Tools and platforms we use
We choose proven, well-supported technology so your product is easy to maintain and easy to hire for later.
- LangChain
- OpenAI
- Claude
- Python
- Pinecone
- pgvector
- FastAPI
AI & Chatbot Development projects we've delivered
A simple, transparent process
No surprises. You always know what's being built, what it costs and when it will be ready.
- Step 1
Discover
A free call to understand your goals, users and budget. You get a clear scope and a fixed or estimated quote.
- Step 2
Design
Wireframes and a clickable prototype, so you see and approve the product before development starts.
- Step 3
Build
Development in 1–2 week sprints with a live staging link. You see progress and give feedback as we go.
- Step 4
Launch & support
Testing, launch and handover — then ongoing maintenance so your product keeps getting better.
What our clients say
Rated 4.9 out of 5 on average by the teams we work with.
“They shipped a RAG assistant in six weeks that our team had been trying to build for a year. Clean code, real answers.”
Marta NdiayeHead of Product, NeuroLedger “Algo Matryx feels less like an agency and more like an extension of our engineering team. Rare combination.”
Daichi WatanabeCTO, Atelier OS “The Flutter build handed to us was the cleanest codebase we've inherited. Everything documented, everything tested.”
Priya RameshEngineering Lead, Orbit
What is a RAG chatbot?
Retrieval-augmented generation (RAG) means the chatbot first finds the most relevant passages in your own documents, then uses an AI model to write an answer from them. The result is far more accurate than a generic chatbot, and every answer can cite its source.
Is our data safe?
Yes. Your documents are stored in a private vector database you control, and we use API settings that keep your data out of model training.
Can the chatbot work on our website and WhatsApp?
Yes. The same assistant can be deployed on your website, inside your app, on WhatsApp or in Slack.
How quickly can we see results?
A working proof of concept on your own data typically takes 2–4 weeks.
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Let's talk about your ai & chatbot development project
Tell us what you want to build. You'll get a reply within one working day — with honest advice, a rough timeline and a free estimate.