Services
AI Systems
We build multi-agent systems to order: from the task statement to a service that runs in your environment.
A task is split into agents with clear roles. An orchestrator routes the steps, keeps the shared context and collects the result. The system works with your data and your tools.
Approach
How we build the systems
We start from the task and the data, not from the model. The architecture stays visible: it is clear which agent did what and why.
- Roles
- Each agent gets a narrow task, an input format and an output format.
- Orchestration
- The orchestrator routes steps, keeps shared context and repeats failed operations.
- Tools and data
- Agents call tools: search, files, internal services, your data sources.
- Control
- Every step is logged. Results that matter stay open for review by a person.
Work
Cases
Internal Telegram assistant for a construction company
- Natural-language dialogue
- Voice messages: speech recognition and spoken replies
- Reminders and task prioritisation
- Morning digest
- Reads PDF, Word, Excel files and photos
- Task assignment to employees
- Automatic switching between work contexts
Autonomous website development pipeline
- Specification, build, QA and deploy agents
- QA as a hard gate with retries
- Agents isolated in sandboxes
- Automatic HTTPS
- Revision loop with the client
Cross-platform local-network file transfer app
- Cross-platform app for the local network
- Pairing by code
- Per-device session tokens
- Recipient confirms acceptance
- Files visible only to the intended recipients
Describe the task — we will answer whether a multi-agent system fits it.
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