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When to Use Statehouse

Statehouse is designed for specific use cases. Here's when it makes sense.

Ideal Use Cases​

AI Agent Memory​

Statehouse excels at storing agent memory:

  • Episodic memory (what happened when)
  • Semantic memory (facts and knowledge)
  • Context across multiple tool invocations
  • Decision history with full provenance

Workflow Orchestration​

For long-running workflows that need:

  • Strong consistency guarantees
  • Crash recovery
  • Audit trails
  • State inspection and debugging

Audit and Compliance​

When you need:

  • Complete event history
  • Deterministic replay
  • Immutable audit logs
  • Provenance tracking

Debugging Agent Behavior​

Statehouse's replay capability makes it ideal for:

  • Understanding why an agent made a decision
  • Reproducing agent behavior
  • Inspecting state at any point in time
  • Debugging complex multi-step workflows

Single-Node Deployment​

Statehouse is perfect when:

  • You need strong consistency
  • You can run a single daemon instance
  • You don't need horizontal scaling (yet)
  • You want simplicity over distributed complexity

Characteristics of Good Statehouse Users​

  • You need strong consistency, not eventual consistency
  • You value correctness and auditability over raw performance
  • You're building agent-based systems or workflows
  • You need to debug and understand system behavior
  • You're comfortable with self-hosted infrastructure

Next Steps​