AI Assistant (OpenClaw)
Press ⌘J anywhere. Create workflows, search flows, debug runs, and manage your workspace through natural conversation. Your AI copilot for automation. Flowgraph's agent layer is inspired by the OpenClaw architecture.
Now accepting early access requests
AI Native
Automation Platform
Describe your workflows in natural language. Flowgraph's AI assistant builds, connects, and orchestrates them - from simple tasks to multi-agent pipelines.
Simple
Bug
VIP
Trigger
New Support TicketZendesk · Webhook Trigger
Triage & ClassifyAI · Intent + Urgency
Customer LookupAgent · CRM + Past Tickets
Smart RouterAI · Route by Complexity
Auto-ResolveKB Answer + Close Ticket
File Bug ReportJira · Notify Engineering
VIP EscalationSlack · Priority Alert
Interactive Demo
Build a flow right here
Pick your pieces, watch them connect, and see a real AI workflow come together in seconds.
Choose a trigger to start your flow
Core Features
Everything you need to automate intelligently
From no-code flows to multi-agent orchestration, built for builders and business teams alike.
Multi-Agent Orchestration
Supervisor-worker architecture where a coordinator LLM delegates subtasks to specialized agents. Build complex AI pipelines without glue code.
600+ Integrations
A growing marketplace of type-safe pieces including Google Sheets, OpenAI, Slack, Discord, and more. Build custom pieces with hot reloading and npm support.
MCP Toolkit
Every piece doubles as an MCP server. Use your automations with Claude Desktop, Cursor, Windsurf, or any LLM client that speaks Model Context Protocol.
Human in the Loop
Pause workflows for manual approval, delay execution, or require human input via chat and form interfaces. Full control over critical decisions.
Code AI Copilot
An in-builder copilot inside every code step. Describe what you need in plain language and it writes production-ready TypeScript or Python for you.
Use Cases
Built for every team
From DevOps incident response to sales pipeline automation. See how teams automate their most critical workflows.
OpenClaw Architecture
Built on an open, composable foundation
Flowgraph's agent layer is inspired by the OpenClaw architecture: open, modular, and composable. Every AI capability is a first-class piece that you can extend, replace, or combine.
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Natural Language → Workflow Describe what you want in plain English. The AI assistant translates intent into executable flow graphs with proper triggers, actions, and routing.
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Autonomous Agents with Tools Agents reason, pick tools (pieces, flows, MCP servers), and iterate until the task is done - all within your governance guardrails.
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Type-Safe Piece Framework Every integration is a fully typed TypeScript npm package with schema validation, hot reloading, and first-class DX.
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RAG & Structured Extraction Ground AI responses in your data with Pinecone/Qdrant vector stores. Extract structured fields from emails, PDFs, and images.
Natural Language Input“Monitor Slack and classify tickets by urgency”
AI Assistant (OpenClaw)Intent parsing → Flow graph generation
Flow EngineSandboxed execution with WebSocket orchestration
Piece Ecosystem600+ type-safe integrations as npm packages
Multi-Agent SupervisorCoordinator → Worker agents → Synthesized output
AI Capabilities
AI woven into every layer
From single-model actions to multi-agent orchestration. Intelligence at every step.
Multi-Agent
Supervisor-worker orchestration with coordinated subtask delegation and synthesis.
Run Agent
Autonomous agent that reasons, selects tools, and iterates until the task is complete.
Ask AI
Analyze data, draft content, make decisions with conversation memory and structured output.
Extract Data
Pull structured fields from text, emails, invoices, images, or PDFs automatically.
Classify Text
Categorize content with custom labels for intelligent routing decisions.
RAG Retriever
Query vector stores to ground AI responses in your own proprietary data.
Write Code
Generate production-ready code from natural language in TypeScript, Python, and more.
MCP Servers
Every piece is an MCP server. Use with Claude, Cursor, or any compatible LLM.
600+
Integrations
11
AI Actions
∞
Custom Pieces
TS + Py
Code Steps
Enterprise Scale
Fine-grained control for mission-critical workflows
Granular resource controls, isolated execution, and elastic scaling. Built for organizations that can't afford downtime.
Step-Level Timeouts
Set execution time limits per step with a slider. If a piece exceeds its budget, it's terminated cleanly. No runaway processes, no config files.
Coming Soon
1hr+ timeouts for long-running ETL, ML training, and batch jobs
Step-Level Memory Control
Configure memory limits per step. OOM events are caught and surfaced as clear errors, not silent crashes.
Coming Soon
Up to 10GB per step for large dataset processing and ML inference
Sandbox Isolation
Every workflow step runs in an isolated sandbox with filesystem, process, and network boundaries. Just select a mode.
Full Sandbox
Code Isolation
Unsandboxed
Elastic Lambda Offloading
Heavy pieces automatically offload to AWS Lambda for elastic scaling. Toggle it on per piece, and the platform handles everything.
In-Sandbox
Lambda Offload
Auto (Hybrid)
FAQ
Frequently asked questions
Everything you need to know about Flowgraph and AI-native workflow automation.
What is Flowgraph?
Flowgraph is an AI-native workflow automation platform that lets you build intelligent automation workflows using natural language. Instead of dragging and dropping blocks manually, you describe what you want in plain English, and Flowgraph's AI assistant builds, connects, and orchestrates the workflow for you - from simple tasks to complex multi-agent pipelines with 600+ integrations.
How is Flowgraph different from Zapier, Make, or n8n?
Flowgraph is AI-native from the ground up, not just AI-assisted. While traditional automation tools require you to manually configure each step, Flowgraph lets you describe workflows in natural language and uses AI to build them. It also features multi-agent orchestration (supervisor-worker architecture), an MCP toolkit that works with Claude, Cursor, and other LLM clients, and enterprise controls like step-level timeouts, memory limits, and sandbox isolation.
What is multi-agent orchestration?
Multi-agent orchestration is Flowgraph's supervisor-worker architecture where a coordinator AI delegates subtasks to specialized agents. For example, a supervisor agent can assign a research task to one agent, a data analysis task to another, and a report writing task to a third - then synthesize the results. This lets you build complex AI pipelines without writing glue code.
What is the MCP Toolkit?
Every Flowgraph integration (called a "piece") doubles as an MCP (Model Context Protocol) server. This means you can use your automations directly from Claude Desktop, Cursor, Windsurf, or any LLM client that supports the Model Context Protocol. Your workflows become tools that any AI assistant can call.
How many integrations does Flowgraph support?
Flowgraph supports 600+ type-safe integrations including Google Sheets, OpenAI, Slack, Discord, Gmail, Notion, GitHub, Stripe, HubSpot, Salesforce, Jira, PostgreSQL, AWS S3, and many more. You can also build custom pieces with hot reloading and npm support using the type-safe piece framework.
Is Flowgraph free?
Flowgraph is currently in early access. You can join the waitlist for free to be among the first to build AI-native automation workflows. Pricing details will be announced closer to the public launch.
Is Flowgraph suitable for enterprise use?
Yes. Flowgraph includes enterprise-grade controls: step-level timeouts (up to 900 seconds, with 1hr+ coming soon), step-level memory control (up to 2GB, with 10GB coming soon), full sandbox isolation for every workflow step, and elastic Lambda offloading for heavy workloads. Every step runs in an isolated sandbox with filesystem, process, and network boundaries.