AI in the software your teams already use

How it works

1. 01

   Observe

   We work alongside your teams and identify the tasks that take up most of their time.

2. 02

   Connect

   We connect the agent to your applications via their APIs, via MCP or, where there is no API, through the user interface itself.

3. 03

   Test

   We check the agent on your real cases before it goes into production.

Offerings

MCP connectors

Your applications opened up to the agent through their APIs or the standard MCP protocol.

Automation without an API

For closed or legacy software, the agent works through the screen, as a person would.

Ask your data

Ask questions about your business data in plain language, with the source for every answer.

Automated testing

Your test scenarios, written in a spreadsheet, replayed with every new release.

Use cases

• All sectors

  Automatic data entry in your software, without modifying it

  The agent navigates the software and fills in fields as a person would, with the user's permissions, without modifying the software.AI in your applications
• All sectors

  Routing pages before ingestion into an assistant

  Each page of a PDF goes either to text extraction or to reading by a vision model, only when that is useful. Ingestion is faster, and costly reading is used only on the pages that need it.AI in your applications
• All sectors

  Measuring adoption and analysing conversations

  Administrators track adoption of the assistant by segment and receive an analysis of conversations: topics, pain points, missing content.AI in your applications
• Software vendors

  Agent-driven regression testing

  An agent drives the browser, replays the scenarios described in a spreadsheet and logs any discrepancies.Azure