vectorize-io/hindsight

Documentation • Integrations • Cookbook • Benchmarks • Paper • Hindsight Cloud [](https://github.com/vectorize-io/hindsight/actions/workflows/release.yml) [](https://pypi.org/project/hindsight-api/) [](https://pypi.org/project/hindsight-client/) [](https://www.npmjs.com/package/@vectorize-io/hindsight-client) [](https://vectorize.io/slack) [](https://opensource.org/licenses/MIT) Hindsight™ is an agent memory system built to create smarter agents that learn over time. Most agent memory systems focus on recalling conversation history. Hindsight is focused on making agents that learn, not just remember. It eliminates the shortcomings of alternative techniques such as RAG and knowledge graph and delivers state-of-the-art performance on long term memory tasks. Contents Hindsight is the most accurate agent memory system ever tested according to benchmark performance. It has achieved state-of-the-art performance on the LongMemEval benchmark, widely used to assess memory system performance across a variety of conversational AI scenarios. The current reported performance of Hindsight and other agent memory solutions as of January 2026 is shown here: The benchmark performance data for Hindsight has been independently reproduced by research collaborators at the Virginia Tech Sanghani Center…