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What is Auteryn?

Auteryn is an AI platform where you build custom AI agents that work like a human — coding, answering customer questions, doing research, browsing the web, and automating complex workflows.

Instead of writing code or managing infrastructure, you describe what your agent should do and connect it to your apps and data. Then you deploy it where your users are.


An Auteryn agent can take on tasks that would normally require a human:

  • Answer customer questions using your company’s documentation and policies
  • Write, review, and debug code with GitHub and a full code execution sandbox
  • Research topics by searching the web, reading documents, and synthesizing findings
  • Automate workflows — answer customer email, respond on Telegram or web widget, send email and update Calendar, Docs and Sheets
  • Use a browser — fill forms, extract data, take screenshots, navigate complex UIs
  • Work in Slack — Internal agents answer in your team’s Slack channels through a Loop (not customer-facing)

Businesses

Deploy customer-facing support agents on your website, WhatsApp, or Telegram — 24/7, at scale.

Engineering Teams

Build internal agents that automate code reviews, run tests, manage issues, and handle DevOps tasks.

Operations Teams

Automate repetitive workflows — data entry, report generation, SLA tracking, ticket triage.

Product Builders

Embed an AI agent directly into your product using our API or web widget — in hours, not months.


Auteryn Chat-only AI Workflow builders Custom LLM apps
Custom agent instructions ✅ ❌ Partial ✅
40+ ready-made Integrations ✅ ❌ ✅ ❌
Knowledge (RAG) ✅ ❌ Partial ✅
Browser / computer use ✅ ❌ ❌ Complex
Deploy to Slack/Telegram/Web ✅ ❌ Partial Complex
No code required ✅ ✅ ✅ ❌
REST API access ✅ Partial Partial ✅

Every agent on Auteryn is built from three things:

1. Instructions — You tell the agent who it is and how to behave. Think of this as a job description.

2. Integrations — You connect the services the agent needs: GitHub, Slack, Google Drive, a database, or any service with an MCP server. The agent uses these to take real actions.

3. Knowledge — You give the agent context: your product docs, your company handbook, your codebase. The agent retrieves the right information at the right time.