What Tablif read on tensemem's site
tensemem describes itself as: “GitHub - tensemem/tensemem: Memory that knows its tenses: embedded, deterministic state memory for AI agents. · GitHub”
- Stage: Beta
- How it differs: “Similarity search returns both “I live in Delhi” and “I moved to Bangalore” and leaves the model to guess. TenseMem keeps one current value per slot”
What it is
Calls itself “memory”.
- Calls itself: memory
“Memory that knows its tenses. Embedded, deterministic memory that AI agents can safely act on.”
Where it puts itself
Its one line of difference: “Similarity search returns both “I live in Delhi” and “I moved to Bangalore” and leaves the model to guess. TenseMem keeps one current value per slot”
“Similarity search returns both “I live in Delhi” and “I moved to Bangalore” and leaves the model to guess. TenseMem keeps one current value per slot”
Who it sells to
Sells to developers.
- Sells to: developers
“Memory that knows its tenses: embedded, deterministic state memory for AI agents.”
How it runs
A API and command-line tool. Runs locally and works offline. Distributed through the npm. Offers an API. Open source. AI is the core of the product. You can bring your own API key.
- Kind: api · cli
- Runs where: on the device, offline
- Distributed via: npm
- API: yes
- Open source: yes
- AI role: core to the product
- Bring your own key: yes
“Python / CLI / REST / MCP API”
“One SQLite file. No server required.”
What it works with
Built on TenseMem Studio. Names FastEmbed, Gemini and 2 more on its pages.
- Built on: TenseMem Studio
- Names: FastEmbed · Gemini · GitHub Copilot · +1
“FastEmbed vectors for search”
“Gemini extract uses GEMINI_API_KEY”
What it offers as proof
In beta. Claims “101”. Trying it asks for an email. Publishes docs.
- Stage: beta
- Number claimed: 101
- Instant signup: yes
- Trial asks for: an email address
“0.1.0 alpha.”
“Sign up”
Sources
Tablif read these pages, last on 27 Oct 2026. Everything above is what the product says about itself; Tablif does not verify every claim.
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