Artificial intelligence
AI solutions for enterprise tasks
We apply AI where it saves people time: parsing documents, answering from the internal knowledge base, video-based control, demand and load forecasting. We start with a pilot on real data — you see accuracy and cost per request before scaling.
What it affects
- faster document handling
- faster document handling0×
- of requests closed by the assistant
- of requests closed by the assistant0%
- assistant availability
- assistant availability0/7
Scope of work
- AI assistants and corporate chatbots
- Document processing and analysis
- Computer vision
- Forecasting
- Intelligent search
- Speech analytics
- Knowledge bases with RAG
- Large language model integration
- On-premises AI model deployment
- AI automation of internal processes
How the work is organised
- 01
A pilot on your data
We measure accuracy on a real corpus before rollout — and say plainly when a task is not solvable yet.
- 02
Answers with a source link
The RAG loop returns the answer together with the document it came from. That makes the result verifiable.
- 03
On premises or in the cloud
If data must stay inside the perimeter, we deploy models on your own GPU hardware sized for the load.
- 04
Human in the loop
Edge cases go to an operator. The model speeds work up but does not make decisions that cannot be wrong.
Let's start
Shall we talk about your digital infrastructure?
Tell us about the task — we will prepare a solution architecture, propose suitable technology and define the next steps.
What happens next
- 1A clarification call or meeting — 30 minutes
- 2A solution outline and preliminary estimate
- 3Hardware and stack specification
- 4A stage plan with timelines and cost