Agent orchestration

Plans, coordinates, acts
Request
Lead agent
Delegates toResearch agent· gathers info from the web

Agents that do the real work

Not a chatbot. These are advanced agents that plan, use real tools, work proactively, and hand off to one another, with you in control.

  • Its hand never touches the database

    An agent has no raw access to your data. It can only call the deterministic flows defined for it, which give the same answer to the same input. The model is left with translating and summarising, the work it is actually good at.

  • Proactive, not just reactive

    Agents can schedule themselves and watch for events with 11 kinds of triggers. Not just the clock: they wake when data changes, when a model drifts, or when an event arrives.

  • Multi-agent hand-off

    Agents pass tasks to specialist agents and coordinate, the way a capable team would.

  • Every agent is an MCP tool

    Each agent is automatically exposed as an API and an MCP tool, so other apps and assistants can use it right away.

  • Searches the web

    Agents pull live information from across the web and turn any link into clean, usable content.

  • Human in the loop

    Pause any workflow for approval on sensitive actions, then resume exactly where it left off.

Bring your own Python

Need something custom? Write your own Python and run it safely in isolation, then use it right inside your data flows and agents.

Isolated and safeYour own librariesUse it anywhere
transform.py
import pandas as pd

def transform(df):
    df = df.drop_duplicates()
    df["clean"] = df["amount"] > 0
    return df.dropna()

# runs in an isolated sandbox

Try it now, see the result.

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