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What is Statehouse?

Statehouse is a strongly consistent state and memory engine designed for AI agents, workflows, and automation systems.

Core Purpose

Statehouse provides durable, versioned, replayable state with clear semantics, so agent-based systems can be debugged, audited, and trusted in production.

What Statehouse Is

  • A strongly consistent state engine
  • Transactional and deterministic
  • Append-only at its core
  • Designed for replay, audit, and explainability
  • Optimized for agent memory and workflow state
  • Built in Rust, with correctness first

What Statehouse Is Not

  • A general-purpose SQL database
  • A vector database
  • A cloud SaaS
  • An eventually-consistent cache

Key Features

Strong Consistency

All writes are transactional. Either a state transition happened, or it did not. There are no partial transactions visible to readers.

Versioning

Every write creates a new version. You can ask:

  • What was the state at time T?
  • How did we get here?
  • What did the agent know when it made this decision?

Event Log

Under the hood, Statehouse is append-only. Snapshots are derived, not authoritative. This enables replay, recovery, auditing, and deterministic debugging.

Replay

Statehouse can replay an agent or workflow's history step-by-step. This is essential for debugging agent behavior, compliance, reproducibility, and trust.

Architecture

Statehouse consists of:

  1. Rust daemon (statehoused): The core state engine, exposed via gRPC
  2. Python SDK: A clean, ergonomic client library that hides gRPC complexity
  3. CLI tools: Command-line utilities for inspection and debugging

The daemon runs locally (or on your infrastructure) and provides a strongly consistent state layer that agents depend on.

Use Cases

Statehouse is designed to be used by agents, not just humans:

  • Agent memory (episodic + semantic)
  • Workflow orchestration state
  • Tool invocation logs
  • Decision provenance
  • Long-running agent coordination
  • Human-in-the-loop checkpoints

Statehouse does not embed models. It provides the ground truth state layer agents depend on.

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