Product Copilots & Agents

Embed agents in your product with REST endpoints, persistent user state, knowledge, and interfaces.

Product engineering teams embed agents so customers can ask questions, work with their data, and take action inside the application. AgentOS gives these teams 80+ REST endpoints for running agents and managing sessions, memory, knowledge, traces, evaluations, and approvals. The same backend can power chat, inline actions, background jobs, and messaging interfaces while keeping user state in one database.

copilot.py

from agno.agent import Agent
from agno.db.postgres import PostgresDb
from agno.models.openai import OpenAIResponses
from agno.os import AgentOS

db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai")

agent = Agent(
    name="Product Copilot",
    model=OpenAIResponses(id="gpt-5.5"),
    db=db,
    add_history_to_context=True,
    num_history_runs=5,
    enable_agentic_memory=True,
)

agent_os = AgentOS(agents=[agent], db=db)
app = agent_os.get_app()

if __name__ == "__main__":
    agent_os.serve(app="copilot:app", port=7777)

This configuration provides an HTTP API, persistent multi-turn history, and per-user memory. Authentication is disabled until you enable it. See Serve as an API for JWT authorization and opt-in per-user isolation.

How product surfaces connect

The agent runs in your AgentOS as a service. Every product surface is a client that calls it over HTTP.

Surface	How it reaches the agent
In-app copilot panel	POST /agents/{agent_id}/runs with user_id and a per-thread session_id
Inline action (“summarize this”, “draft a reply”)	The same endpoint, a short-lived session_id
Slack / Telegram / WhatsApp	An interface adapter maps the channel onto runs and sessions
Backend event (webhook, cron)	A custom FastAPI route calling agent.arun(...)

Stored memory can follow a user when surfaces call the same agent with the same user_id and database. Session history continues only when they also reuse the same session_id. Messaging interfaces usually create surface-specific session IDs.

Choose a path

You have	You want	Start with
A B2B SaaS product	JWT authentication and opt-in per-user isolation	Serve as an API
Users in Slack or the browser	The same agent where they already work	Interfaces
An indexed document corpus	Answers grounded in retrieved content	Knowledge agents
Live systems such as Slack, Drive, or databases	Current records queried at run time	Connecting your data
Multi-day user relationships	Memory that persists per user across surfaces	Sessions and memory

Explore

Serve as an API

Turn the agent into an HTTP service with streaming, sessions, and auth.

Sessions and memory

Store multi-turn history and per-user memory in the configured database.

Connecting your data

Give the agent access to Slack, Drive, databases, and MCP servers.

Interfaces

Connect Slack, Telegram, WhatsApp, and browser clients through interface adapters.

Developer Resources

• Runtime overview
• Sessions
• Memory
• Scout template