vectorize-io/hindsight

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What is Hindsight?
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**
- Memory Performance & Accuracy
- Quick Start — server · clients · platforms · embedded
- Adding Hindsight to Your Agent — LLM Wrapper · integrations · coding agents · MCP
- Core Concepts — memory types · retain / recall / reflect · observations · mental models & knowledge pages · banks
- Use Cases
- Running in Production
- Resources
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Memory Performance & Accuracy
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:
> Live, continuously updated results — including per-model accuracy, latency and cost — are published at benchmarks.hindsight.vectorize.io.
The benchmark performance data for Hindsight has been independently reproduced by research collaborators at the Virginia Tech Sanghani Center for Artificial Intelligence and Data Analytics and The Washington Post. Other scores are self-reported by software vendors.
Hindsight is being used in production at Fortune 500 enterprises and by a growing number of AI startups.
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> 🤖 **Using a coding agent?** Install the Hindsight documentation skill for instant access to docs while you code:
>
> Works with Claude Code, Cursor, and other AI coding assistants.
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Quick Start
1. Start a server
Docker (recommended)
>API: http://localhost:8888
>UI: http://localhost:9999
Hindsight works with **25+ LLM providers** via HINDSIGHT_API_LLM_PROVIDER — hosted (openai, anthropic, gemini, groq, bedrock, vertexai, minimax, deepseek, atlas, meta, …), fully local (ollama, lmstudio, llamacpp), any OpenAI-compatible endpoint, and gateways (litellm, litellmrouter) that reach the rest. Existing subscriptions work too: openai-codex (ChatGPT Plus/Pro), claude-code (Claude Pro/Max), cursor (Cursor) and github-copilot (GitHub Copilot) need no API key. See supported models.
Docker (external PostgreSQL)
> Oracle AI Database is also supported for enterprise deployments with full feature parity. See the storage documentation for details.
Bare metal (pip)
Kubernetes (Helm)
Managed (no server)
Hindsight Cloud is the hosted option: managed infrastructure that scales automatically, plus a dashboard, backups, team collaboration and a 99.9% uptime SLA. Billing is usage-based with free credits to start — no fixed monthly or per-seat fee. Point any client at https://api.hindsight.vectorize.io with your API key and skip the deployment entirely.
Compare self-hosted, Cloud and Enterprise → · Sign up →
All options, including Windows and air-gapped setups, are covered in the installation guide.
2. Connect a client
Python
Node.js / TypeScript
Full reference: Python · Node.js · Go · CLI · REST API
Supported Platforms
| Platform | Docker | Bare Metal (pip) | Embedded DB (pg0) |
|----------|--------|------------------|--------------------|
| **Linux** (x86_64, ARM64) | ✅ | ✅ | ✅ |
| **macOS** (Apple Silicon / arm64) | ✅ | ✅ | ✅ |
| **macOS** (Intel / x86_64) | ✅ | ⚠️ | ✅ |
| **Windows** (x86_64) | ✅ | ✅ | ✅ |
⚠️ Intel Macs: use hindsight-all-slim — see the installation guide for details.
Python Embedded (no server required)
On Intel (x86_64) Macs, install hindsight-all-slim instead — see Supported Platforms.
A Node.js equivalent and a daemon CLI are also available.
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Adding Hindsight to Your Agent