Tenure
Persistent state management for AI systems — gives AI memory with versioned beliefs, scope isolation, and audit trails
| What is it | Persistent state management for AI systems — gives AI memory with versioned beliefs, scope isolation, and audit trails |
|---|---|
| Pricing | Unknown |
| Platform | Web Application |
| API | Yes |
| Best for | preventing AI memory drift across projects, maintaining audit trails for AI decisions |
| Domain registered | 2026 |
Data updated June 11, 2026
What does Tenure do?
Tenure is a state management system designed specifically for AI applications. It provides persistent, governable memory that survives across sessions and tools, replacing the typical context window approach with structured belief storage. Instead of relying on vector search and similarity matching, Tenure uses hard scope boundaries and precise querying to ensure only relevant information gets injected into AI responses.
The system works by extracting decisions, preferences, and facts from AI interactions and storing them as versioned beliefs with complete provenance. Each belief has an origin, scope, version history, and audit trail. What sets Tenure apart is its observation mode—you can run it with extraction enabled but injection disabled for weeks, reviewing exactly what it learns about your workflow before allowing it to influence any AI responses. This eliminates surprises and gives you complete control over what the AI knows.
Developers and engineering teams benefit most from Tenure, particularly those working across multiple projects who need to prevent knowledge contamination between different codebases or clients. It integrates with VS Code, mobile apps, and any OpenAI-compatible client through a local deployment that routes requests through its state layer while preserving your existing API keys and model choices.
Key features
What makes it stand outWho is Tenure for?
Who benefits most from this toolTrust & presence
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