01
Enquiries, leads and bookings
Customer replies, request qualification, service selection, booking and a complete handover to a person or CRM.
- Website and messengers
- Human handover
- Conversation quality control
AI implementation
AI agents and business process automation
We design AI agents, RAG systems and controlled automations that work with enterprise knowledge, perform approved actions and fit existing workflows.
We work with companies in Belarus and remotely with project teams across Europe and the CIS.
- 01AI agents
- 02RAG and enterprise knowledge
- 03CRM · ERP · APIs
Use cases
Where an AI agent creates practical value
We start with a measurable task and clear constraints. The agent receives only the data, tools and permissions it needs.
02
RAG and enterprise search
Search across documents and knowledge bases with access control and links to the sources used in each answer.
- Policies and instructions
- Internal knowledge bases
- Source-grounded answers
03
Actions in business systems
Document preparation, notifications, status updates and other approved operations through APIs and integrations.
- CRM and ERP
- Internal APIs
- Audit log for every action
Architecture
A controlled part of the workflow, not chat for its own sake
Knowledge, the model, tools and permissions are separated. Unusual cases go to a person and every action can be reviewed in the audit log.
- 01
Goal and boundaries
Define the workflow, users, risks and acceptance criteria.
- 02
Knowledge and data
Identify sources, data quality and access rules.
- 03
Tools and control
Restrict actions and add human handover and error handling.
- 04
Integration and observability
Connect systems, tests, logs, monitoring and support.
Deliverables
What the team keeps after launch
We define the deliverables before development so a pilot does not become a closed demonstration with no practical next step.
- 01
Workflow map and target architecture
- 02
Working agent with agreed integrations
- 03
Acceptance and negative test scenarios
- 04
Access, logging and support documentation
Public evidence
Chota Agents — our product for enquiries and bookings
The product demonstrates a practical workflow: an agent replies to customers, captures leads, helps with booking and passes data into the operating process.
AI agent questions
What to agree before the pilot
Which processes can an AI agent handle?
Common scenarios include customer enquiries, lead qualification, bookings, enterprise knowledge search, document preparation, notifications and approved actions in CRM, ERP or internal systems.
How is an AI agent different from a conventional chatbot?
A conventional chatbot usually follows a predefined flow. An AI agent can use context, work with a knowledge base, call approved tools and hand unusual situations over to a person.
Can the solution run inside our environment?
Yes. We select cloud, private or hybrid deployment according to data and infrastructure requirements. Access controls, logging and data-handling rules are agreed before the pilot.
How do you validate the agent's answers and actions?
Before launch, we build a set of acceptance scenarios covering answers, actions, access limits, human handover and error handling. After launch, quality is monitored against agreed indicators.
Who owns the code, data and project outputs?
Ownership, deliverables and the terms for any models or external services are defined in the contract and technical specification before development starts.
First step
Show us the workflow — we will identify where an agent genuinely fits
In the first meeting, we review the current process, data, integrations, constraints and a practical way to validate the result.
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