hindsight: Not an AI that remembers, but an AI agent that learns
vectorize-io/hindsight
About the project
While most agent memory systems focus on restoring conversation history, Hindsight focuses on building agents that learn over time. It overcomes the limitations of RAG and knowledge graphs, achieving SOTA performance on long-term memory tasks.
Through three core actions—retain, recall, and reflect—it stores and retrieves information to generate responses tailored to user preferences. It delivers independently verified accuracy on the LongMemEval benchmark and is in production at Fortune 500 companies.
Using a Wrapper approach that encloses existing LLM clients, you can add memory functionality with just two lines of code. It supports over 25 LLM providers, including OpenAI and Anthropic, as well as local models, and offers clients for Python, Node.js, Go, and more.
vectorize-io/hindsight
Hindsight: Agent Memory That Learns
Python
This introduction was generated automatically by AI. Check the original for the author's claims and context. Copyright belongs to the original author.
Our guide explains how the AI works. Report errors, attribution issues, or removal requests via Contact.




