Hindsight

What is Hindsight?

Hindsight is an agent memory system from Vectorize that gives AI agents durable memory across sessions. Your application stores material with a retain call and queries it with recall, organized into separate memory banks, such as one bank per user plus a shared bank for product documentation. The open-source engine is MIT licensed, self-hosted and stores memories in PostgreSQL, with Python and other SDKs, an API and MCP support. Vectorize also runs Hindsight Cloud, a multi-tenant managed service billed pay as you go with credits, and Hindsight Enterprise, a single-tenant deployment in a private cloud, your own AWS, Google Cloud or Azure account, or on premises. Enterprise adds SSO, MFA, audit logs, Memory Defense for redacting secrets and blocking prompt injection, GDPR data controls and Hindsight Memlake, which keeps memories in object storage for very large banks. Vectorize does not publish dollar prices for Cloud or Enterprise, so ask the vendor.

Use cases

• Give agents long-term memory
• Personalize support agents per user
• Share product knowledge across agents
• Redact secrets before memory is stored
• Scale memory to very large banks
• Add memory through MCP or SDKs

Who it's for

• AI engineers
• Agent developers
• Enterprise platform teams

Why use Hindsight

• A simple retain and recall interface lets agents remember users and prior outcomes instead of replaying whole chat histories.
• Separate banks keep each user's memory isolated while documentation is indexed once and shared.
• The MIT license and self-hosting option mean you can run it in your own environment at no software cost.
• Managed Cloud lets teams start without operating a database or the memory service.
• Enterprise options cover private networking, SSO, audit logs and data privacy needs.

Hindsight features

• Retain and recall API for agent memory
• Memory banks for per-user and shared knowledge
• Python client, API and MCP integration
• MIT-licensed self-hosted engine on PostgreSQL
• Hindsight Cloud with pay-as-you-go credits
• Memory Defense for secrets and prompt injection
• Role-based access and scoped API keys
• Single sign-on and MFA on Enterprise
• Audit logs, webhooks and SIEM streaming
• Hindsight Memlake object-storage memory
• Private cloud, BYOC and on-premises deployment

Hindsight integrations

• PostgreSQL
• Okta
• Microsoft Entra ID
• Google Workspace
• AWS
• Google Cloud
• Azure
• Kubernetes
• OpenAI

How to get started with Hindsight

1. Choose how to run it: self-host the open-source engine, sign up for Hindsight Cloud, or arrange Enterprise.
2. Create memory banks with the client, for example one per user and one for shared documents.
3. Call retain to store conversations or facts, and call recall with a query when the agent needs context.
4. Pass the recalled memory into your agent prompt, and add integrations, MCP or Enterprise controls as you scale.

Hindsight limitations

• Hindsight Cloud and Enterprise prices are not published; ask the vendor
• The pricing page on the docs site returns a not-found error
• Memlake, SSO, MFA, audit logs and webhooks are Enterprise features
• Self-hosted Hindsight is run and maintained by you
• PostgreSQL storage suits banks under roughly 50,000 memories each

Hindsight pricing

Hindsight is open source, so you can use and self-host it for free.

Hindsight plans

• Open source

  Free

  self-hosted, MIT licensed

  • Memory engine on PostgreSQL
  • Self-managed deployment
  • Documented on the open-source site

• Hindsight Cloud

  Price on vendor site

  pay as you go with credits

  • Multi-tenant, fully managed
  • MCP, SDKs and API
  • Agent framework integrations

• Hindsight Enterprise

  Custom

  annual or contract billing

  • Private cloud, BYOC or on-premises
  • SSO, MFA and audit logs
  • Memory Defense
  • Hindsight Memlake

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

Hindsight alternatives

The main Hindsight alternatives listed on Debuly are Mem0, Zep, Letta, Supermemory, Cognee and LangMem. The table compares pricing and platforms; order is A–Z.

1. 

   Cognee

   Open-source memory engine for AI agents that combines vector search, knowledge graphs and relational storage, with a hosted cloud.

   Developer platformsAutomation and agentsResearch and search
   FreemiumVisit Cognee (official site)
2. 

   LangMem

   Python library from LangChain that gives AI agents long-term memory and lets them refine behavior from past conversations.

   Developer platformsAutomation and agents
   Open sourceVisit LangMem (official site)
3. 

   Letta

   Platform, formerly MemGPT, for building stateful AI agents with persistent memory, from a terminal app, SDK or API.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Letta (official site)
4. 

   Mem0

   Memory layer for AI agents and apps, available as an open-source package or a managed platform that keeps user context across sessions.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Mem0 (official site)
5. 

   Supermemory

   Memory and context API for AI agents with user profiles, a memory graph, retrieval and connectors, billed by usage.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Supermemory (official site)
6. 

   Zep

   Managed memory and context platform for AI agents, built on the Graphiti knowledge graph, with Python, TypeScript and Go SDKs.

   Developer platformsAutomation and agents
   FreemiumVisit Zep (official site)

Hindsight FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from hindsight.vectorize.io · fetched 23 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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