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Vectorize

Agent memory that learns

About Vectorize

Vectorize provides Hindsight, an open source agent memory system that lets agents remember users, persist context across sessions, and improve over time. It targets developers and teams building AI-powered agents who need memory beyond one-off responses and want an architecture that can scale with multiple agents and users.

Hindsight operates as a memory layer that can be integrated with existing agents and workflows. It supports per-user memory, cross-session persistence, and fast recall, while remaining model-agnostic so different LLMs can be swapped without losing learned knowledge.

The system emphasizes learning from mistakes by turning user corrections and tool-call failures into experiences. A reflection layer synthesizes facts into reusable knowledge, and curated mental models guide common situations for better judgment.

Hindsight is available in open source form under MIT license for self-host deployment, as a cloud service with usage-based pricing, and as an enterprise deployment with private cloud options. It is designed to work with a variety of integrations and provides a REST API, SDKs, and an MCP server for different languages and environments.

Use cases

  • Developers building AI agents who need long-term memory across conversations.
  • Teams deploying multiple agents that benefit from shared context and per-user personalization.

Key features

  • Per-user memory
  • Cross-session persistence
  • Fast memory recall
  • Works with any LLM
  • Integration-ready
  • Open source and MIT licensed

Pros and cons

Pros

Open source memory system with MIT license

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