TenseMem is listed as Open Source. Check https://github.com/tensemem/tensemem for the current plan limits, as vendors change pricing frequently.

What is TenseMem best for?

TenseMem is commonly used for Agent memory, State tracking, Local-first storage. It supports English.

TenseMem

Q: What is TenseMem?

TenseMem is a code AI tool listed on Use AI Tools. TenseMem is embedded, deterministic state memory for AI agents, described as memory that knows its tenses. One SQLite file with no server: the model proposes typed facts and the engine decides what is current, keeping one current value per slot, reporting whether a read is fresh and refusing to learn from its own output. Installed with pip, it works with a rule-based extractor or with OpenAI, Anthropic, Ollama, LiteLLM or Gemini.

Code⚡ Advanced✅ Global access

Agent memoryState trackingLocal-first storage

Open SourceEnglish

TenseMem is embedded, deterministic state memory for AI agents, described as memory that knows its tenses. One SQLite file with no server: the model proposes typed facts and the engine decides what is current, keeping one current value per slot, reporting whether a read is fresh and refusing to learn from its own output. Installed with pip, it works with a rule-based extractor or with OpenAI, Anthropic, Ollama, LiteLLM or Gemini.

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🎯 Real-World Use Cases

Replace stale duplicate facts

Similarity search returns both an old address and a new one; TenseMem keeps one current value per slot.

Run without an API key

The bundled FakeExtractor is rule-based, so the same API works offline.

Check freshness before acting

A read returns whether the value is current, not just the nearest match.

⚖️ Honest Review

✅ Pros

+Single SQLite file with no server to operate
+Deterministic: the engine, not the model, decides what is current
+Refuses to learn from its own output

⚠️ Cons

−Python package, so Python agents get the smoothest path today
−Opinionated memory model that replaces rather than augments vector search

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CodeOct 24, 2026