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FIXPOINT
Open-source infrastructure for stateful AI agent workflows
Apache-2.0
ABOUT
Building reliable AI agent workflows is difficult because most LLM integrations are stateless — they lose context between turns, can't handle multi-step processes that require human approval, and have no built-in durability. Fixpoint solves this by providing open-source infrastructure for stateful, multi-step AI workflows with persistent memory, human-in-the-loop checkpoints, and agent orchestration. Teams can build agents that remember past interactions, pause for human review, and coordinate across multiple specialized agents — all without building custom state management, retry logic, or coordination infrastructure.
INSTALL
pip install fixpointINTEGRATION GUIDE
1. Build customer support agents that maintain conversation state across multiple turns and can escalate to humans when needed
2. Create document processing pipelines where agents extract, validate, and summarize data with human review at each stage
3. Deploy multi-agent workflows where a orchestrator agent delegates sub-tasks to specialized agents and synthesizes results
4. Automate research workflows that require persistent memory across sessions, web searches, and iterative refinement
5. Build AI-powered data enrichment pipelines that combine multiple data sources with human verification checkpoints
TAGS
agent-orchestrationworkflowsstateful-agentshuman-in-the-looppython