Agents that serve customers and do the work.
Agents AI · Agents that execute
Build agents with your knowledge base and the tools they're allowed to use — calendar, spreadsheet, CRM or your system's API. They work as a team, on your channels, and only claim what they actually did.
What Agents AI does
Agent builder
Instructions, tone of voice, knowledge base, tools and rules for each agent, on one screen.
Multi-agent pipelines
Reception, specialist and scheduling agents passing the conversation between them, with an orchestrator deciding who speaks.
A real knowledge base
Documents, articles and your website indexed for semantic search, with internal content kept separate from public.
Tools
Google Calendar, spreadsheets, CRM, a calculator and any REST API from your system, with credentials stored encrypted.
On your channels
WhatsApp, site chat and Telegram with the same brain — and voice, through a voice agent integration.
Model and cost under control
Choose each agent's model and track usage per company, within your allowance.
How it works
- You describe the work — The setup assistant builds the agent team based on what your operation needs.
- Connect knowledge and tools — Documents, website, calendar, spreadsheets and your system's API.
- Test before going live — Chat with the agent, run conversation tests and see every tool it called.
- Turn it on in a channel — WhatsApp, site chat or Telegram — and monitor the quality of every conversation.
Safeguards that don't depend on the prompt
Quality is held by mechanisms in the engine, not instructions the model can ignore.
- Won't claim it booked, recorded or sent something unless the action happened
- Won't make up an address, phone number or ID that didn't come from a source
- Escalates to a person when a tool keeps failing
- A quality judge reviews conversations and points out where to improve
Differentiators
Doesn't pretend it did it
If the agent says it booked the appointment, there's a calendar record to prove it. Without a record, the message never reaches the customer.
Real customer context
The agent reads the customer's history and commitments in the CRM — and what it does goes back to the same record.
Measured quality
Conversation tests with simulated customers and analysis of real conversations, to fix issues before customers notice.
How it connects to the rest of the platform
- CRM: channels and customer history
- AI Teams: agent teams with a manager
- Nextflow: agents inside a process
Frequently asked questions
Which AI model is used?
Agents run on AWS Bedrock models (such as Claude and Amazon Nova), chosen per agent. Your data is not used to train third-party models.
Can the agent book on my calendar?
Yes, by connecting Google Calendar. The agent checks open slots, creates the event and only confirms to the customer after it's created.
What if the agent doesn't know the answer?
It says it doesn't know and offers a person from your team. You decide when it hands off and to which queue.
Can I test before putting it on WhatsApp?
Yes. There's a test chat, simulated-customer tests and a test copy to validate changes without affecting real customer service.