Vectorize
A RAG and agent-memory platform, including open-source Hindsight to give AI agents persistent memory across conversations
What is it
Vectorize is a platform focused on RAG (retrieval-augmented generation) and AI-agent memory, including the open-source Hindsight system to give agents persistent memory across different conversation sessions. That is, the agent doesn't "lose its memory" every time a new conversation starts but can remember the context accumulated earlier.
What problem it solves
Large language models themselves have no long-term memory; agents often start from scratch each interaction, losing prior preferences, decisions, and context, so users have to repeat themselves again and again. Implementing cross-conversation memory yourself isn't easy, involving data storage, retrieval, and updating.
Vectorize provides RAG capability on one hand, letting agents retrieve external knowledge to answer questions; and uses Hindsight to handle agent memory on the other, letting information be preserved and accessed across conversations — and it's open-source, so teams can inspect and deploy it themselves. This makes building agents that "remember things" more practical. It suits developing long-term conversational assistants, AI products needing to accumulate user context, and engineering teams building RAG applications.
Key Features
- Provides RAG retrieval-augmented generation capability
- Persistent agent memory across conversation sessions
- Includes the open-source Hindsight memory system
- Lets agents accumulate and access long-term context
- Open-source components you can inspect and deploy yourself
- Suited to long-term conversational AI applications
Pros
- Lets agents remember context across conversations, reducing repetition
- Hindsight is open-source, so teams can control and self-host
- RAG and memory integrated on one platform
Cons
- Adopting a memory system requires considering privacy and data governance
- Leans toward development teams with engineering capability
Use Cases
- Building long-term conversational assistants that remember user preferences
- Building persistent cross-conversation memory for AI agents
- Combining external knowledge with historical context in RAG applications
Editor's Note
Pairing RAG with cross-conversation memory and open-sourcing Hindsight — a great fit for building agents that remember things.
FAQ
Is Hindsight open-source?
Yes — Hindsight is an open-source memory system provided by Vectorize, giving agents persistent memory across conversations, and teams can inspect and deploy it themselves.
How does it differ from ordinary RAG?
Beyond RAG's external-knowledge retrieval, Vectorize specifically adds agent memory, letting information be preserved across conversations rather than starting from scratch each time.
Which applications is it suited to?
Suited to long-term conversational assistants needing to accumulate user context, AI-agent products, and engineering teams building RAG systems.