AI Agents & LLM Integration
We put large language models to work on real operational tasks: reading supplier invoices and prescriptions, answering questions about your sales in plain English, summarising a team's day, and giving assistants like Claude or ChatGPT safe, permission-checked access to your systems through MCP servers. Our own products ship these capabilities in production.
Outcomes you can expect
- Hours of data entry replaced by review-and-approve
- Managers get answers without waiting for a report
- AI access that respects the same roles as your users
Tools & platforms
- OpenAI
- Claude
- Llama (Ollama)
- MCP
- Vercel AI SDK
- Python
- PostgreSQL
What we deliver
- 01
Document extraction
Turn invoices, receipts, delivery notes and résumés into structured records with validation.
- 02
Natural-language reporting
Ask 'what sold best last week in Doha?' and get the table and the chart.
- 03
MCP servers
OAuth-secured Model Context Protocol servers so AI assistants can act within user permissions.
- 04
Knowledge assistants
Retrieval-augmented chat over your policies, manuals and product catalogue.
- 05
Voice & chat agents
Assistants that take actions — create a task, apply leave, check stock — not just answer.
- 06
Private models
Self-hosted Llama-family models when data cannot leave your network.
Where we already run this in production
Common questions
Is our data used to train public models?
No. We use API configurations that exclude your data from training, and we can run open models on your own servers when data must stay in-house.
What is an MCP server?
The Model Context Protocol lets AI assistants call tools in your systems. We build MCP servers that authenticate each user, so the assistant can only do what that person is allowed to do.
Ready to talk ai agents & llm integration?
Tell us about it. A solution architect replies within one business day with next steps — no sales script.