DEPT 01AI department
AI that runs on
your own data
On-premise language models, fine-tuning on your organisation’s data, RAG and knowledge bases, AI agents and machine vision — from feasibility to deployment.
One request,
the right route
02/05LLM Router · playground
Write a prompt and watch the router pick a model — and see why. Cost, latency and where the data is processed are all visible.
Why this model?
Persian legal text + sensitive data → a model fine-tuned on your data, on your own server.
| Task | Model | Latency | Cost |
|---|---|---|---|
| Fast, low-cost answers | fast-small | 120ms | 1× |
| Multi-step reasoning | reasoning | 2.4s | 8× |
| Persian legal fine-tune | fa-legal-ft | 640ms | 2× |
| Code and data | code | 900ms | 4× |
| On-premise, data stays in | on-prem-llm | 780ms | 0× |
Tap a row to compare a manual choice with the router’s pick.
Latency and cost are relative and illustrative; routing is simulated with in-browser rules.
From data to agents,
layer by layer
03/05The AI stack
Making an organisation intelligent is a five-layer stack. Scroll and the layers separate; each shows exactly what the team delivers.
L04 · Deliverables
- Autonomous agents with tools and memory
- Multi-agent systems
- Q&A assistant and smart search
A neural map
of capabilities
04/05Capabilities
Capabilities are neurons; products sit on the synapses. Hover a neuron to light up its paths and the real products built on it.
The AI
assembly line
05/05Process
A project travels the conveyor like a part. Scroll and the package — the logo chip — moves on; each station stamps its output.
01 · This station’s output
- Requirements and acceptance criteria
- Data and risk assessment
FAQ
What is Enterprise LLM & Fine-tuning?
On-premise deployment of language models on your infrastructure, training and fine-tuning on your data, and RAG knowledge bases — without data leaving the organisation.
What is AI Agents & Assistants?
Autonomous agents and multi-agent systems that plan, search, call tools and report automatically — built with LangGraph, CrewAI and MCP.
What is Machine Vision?
People counting, face recognition and matching, liveness and OCR — detection models trained and deployed on CPU or GPU, even fully offline.
How does work in AI & Intelligent Transformation start?
With a discovery session and a small pilot that has a clear success metric; once results are in, the work expands in phases.
Tell us your project in one sentence — we’ll find the right facet together.
Start the conversation