Support that knows your rules

The agent answers from the knowledge base with a source link, checks the order in the CRM and creates a ticket. Anything beyond its authority goes to an operator — with the context.

01Builder

Sketch your AI agent’s architecture

Pick tasks, sources, actions and the autonomy level — the diagram appears on the right: employee, agent, data, approval and actions.

01 · Tasks
02 · Data sources
03 · Actions
04 · Autonomy
Preliminary architectureNodes: 9
Preliminary AI agent architecture for the selected options
  1. Employee → Agent runtime
  2. Customer channel → Agent runtime
  3. Agent runtime → Guardrails · audit, LLM, Docs · RAG, CRM, Reply to user, Create ticket
  4. Guardrails · audit
  5. LLM
  6. Docs · RAG
  7. CRM
  8. Reply to user
  9. Create ticket
AGENT
Support agent

CONTEXT
Docs · RAG · CRM

ACTIONS
Reply to user · Create ticket

CONTROL
Acts within tool permissions · Role-based access to sources · Audit log of every tool call

This is a preliminary outline. The architecture may change once we review the process and the data.

02AI Support

Where the line is

We define upfront what the agent decides itself and what it hands to a person: refunds above a limit, complaints, unusual cases.

  • Answers only from the current knowledge base
  • Handover to an operator with the conversation history
  • A log of every action

Would a scripted FAQ bot be enough?

Support botsBotZone
04Contact

What do you want to hand to AI?

Describe the task in your own words, answer five questions and get a preliminary AI agent schema. Or just write to us.

Preliminary AI agent schema

Step 1 of 7

Just message us on Telegram