Introduction to Hindsight Cloud

Hindsight Cloud is the managed, self-serve service for Hindsight, agent memory that learns. Sign up, create a memory bank, and give your agents long-term memory through pre-built integrations with the agent frameworks and AI tools you already use, MCP, the Python and TypeScript SDKs, or the API, with nothing to deploy or operate. See Integrations.

Memory that learns

AI agents forget everything between sessions. Without memory, every conversation starts from zero: no context about who the user is, what was decided, or what the agent has already learned.

Storing conversations and searching them later isn't enough. A useful memory has to answer "what did Alice tell me last spring?" (time), connect "Alice works at Google" with "Google is in Mountain View" (relationships), and notice that a user who kept asking for functional code prefers functional programming (learning).

Hindsight is a memory system that learns. It doesn't store transcripts. It extracts what was said into facts, links them, and keeps consolidating them into durable knowledge in the background, so what your agent knows gets better the more it's used.

How a bank learns

Each memory bank is a separate memory for one agent, user or context. Knowledge in a bank builds up in layers:

Layer	What it is	Example
World fact	An objective claim the bank was told	"Alice works at Google."
Experience fact	Something the agent itself did	"I recommended Python to Bob."
Observation	A belief consolidated from many facts, with its evidence and its history	"The user was a React enthusiast and has now switched to Vue."
Mental model	A curated, pre-computed answer to a question you ask often	"What are our team's communication norms?"
Knowledge page	A living document the bank writes about itself, kept in a browsable knowledge base	"Architecture / How the billing service works"

1. Retain: extract facts and link them

Retain turns content (messages, documents, files) into typed facts. Each fact is linked to the entities it mentions and to other facts that share them, building a graph. That graph is what makes "where does Alice work?" answerable from two facts that were never stored together. Time is captured too, so facts can be placed on a timeline.

2. Consolidate: turn facts into observations

After every retain, a background process consolidates new facts into observations: the bank's durable beliefs.

• Deduplicated. Overlapping facts merge into one observation instead of piling up as repeats.
• Evidence-grounded. Each observation points at the memories that support it, with exact quotes and a count of supporting evidence.
• Refined, not overwritten. New evidence updates an observation and its history is kept, so you can see a belief change over time.
• Freshness-aware. When new memories haven't been consolidated yet, reflect treats the affected observations as possibly stale and checks them against the raw facts before relying on them.

Consolidation is automatic. There's nothing to schedule or call.

3. Synthesize: mental models and knowledge pages

Observations answer one question at a time. For the questions that matter most, the bank keeps synthesized answers ready:

• Mental models are curated summaries you define for a question you ask often, such as "What are this customer's preferences?" They are the fastest, most consistent answer to that question. A mental model can refresh on demand, on a schedule, or automatically after consolidation brings in new knowledge in its scope.
• Knowledge pages are living documents the bank writes about itself, organized in folders in the bank's Knowledge base, like a wiki that keeps itself current. Each page answers one question, is built from the bank's observations rather than raw conversation, and is rewritten incrementally whenever consolidation produces new knowledge in its scope. Pages never read other pages, so they can't cite each other into a feedback loop. Browse them in the console's Knowledge base view, or read and manage them over the API under /v1/default/banks/{bank_id}/knowledge-base/.

Using what a bank knows

Recall: retrieve memories

Recall runs four searches in parallel, because no single strategy handles every question (this is the TEMPR strategy):

Method	What it finds
Semantic	Memories similar in meaning, even with different wording
Keyword (BM25)	Exact names and technical terms
Graph	Memories connected through shared entities, even with no words in common
Temporal	Memories in a time window ("last week", "in March")

Results are fused by rank, so a memory several strategies agree on wins, then re-ranked by a model that reads the query and each memory together. You set a token budget rather than a result count: Hindsight fills the context you can afford with the most relevant memories.

Reflect: get an answer

Reflect returns an answer rather than a list of memories. It runs an agentic loop over the bank, checking its knowledge in priority order: mental models first, then observations, then raw facts. That order gives fast, consistent answers to known questions while still reaching the detail behind them.

Shaping how a bank reasons

Each bank can be configured to reason the way your agent should:

• Mission. A natural-language statement of what the bank is for, which tells Hindsight what to prioritize. For example: "I am a research assistant specializing in ML. I prefer simplicity over cutting-edge."
• Directives. Hard rules reflect must follow, such as "Never recommend specific stocks" or "Always cite sources."
• Disposition traits. How the bank weighs information: skepticism (trusting to skeptical), literalism (flexible to literal) and empathy (detached to empathetic).

The mission gives the interpretive lens, directives enforce boundaries, and disposition modulates reasoning style. See Memory Banks for how to configure them.

Hindsight Cloud Features

Hindsight Cloud runs Hindsight for you and adds everything around it:

• Managed Infrastructure - No servers to deploy or maintain, and models (LLM, embeddings, reranking) included
• Integrations - Pre-built integrations for agent frameworks, coding agents and AI tools, plus MCP, a REST API, and Python and TypeScript SDKs
• Team Management - Invite team members with role-based access control
• Usage Analytics - Real-time dashboards showing consumption
• Credit System - Usage-based pricing with credits for API operations

Usage-Based Pricing

You pay for what you use, from a prepaid credit balance:

• Per token: retain (content stored), recall (memories returned), retrieving a mental model or knowledge page, and enhanced file extraction
• Per call: reflect, and creating or refreshing a mental model or knowledge page
• Storage: memories held longer than 30 days, billed daily

See Billing for current rates.

Enterprise features

Some capabilities are Enterprise features. They're enabled by the Hindsight team per plan or contract — they aren't self-serve. To turn one on, book a call or contact your Hindsight representative. In the console, each Enterprise feature also shows a book a call button when it isn't enabled for your organization. See Hindsight Cloud with Enterprise features for how this works.

Feature	What it does	Learn more
Single Sign-On (SSO)	Sign in with your identity provider (Okta, Microsoft Entra ID, Google Workspace); members are auto-provisioned on first sign-in. Managed on the Team page.	Single Sign-On
Enforced MFA	Require multi-factor authentication for everyone in your organization.	MFA
Memory Defense	Advanced detectors and redaction — secret detection, prompt-injection screening, LLM screening, and more — beyond the free regex-based redaction.	Memory Defense
Data Privacy (GDPR)	Erasure, retention and export of a person's data across your banks.	Data Privacy
Audit Logs	A per-bank record of who did what, and when.	Audit Logs
Webhooks & SIEM	Stream organization events to your webhook endpoints or SIEM.	Webhooks & SIEM
Enterprise Support	A ticket portal, email intake, a shared Slack channel and contracted response times.	Enterprise Support

Need a dedicated deployment?

Hindsight Cloud is a shared, multi-tenant service. If you need a single-tenant deployment — in our cloud, your own AWS, Google Cloud or Azure account, or on premises — with private networking, see Hindsight Enterprise.

Getting Started

Ready to give your AI agents persistent memory? Head to the Getting Started guide to create your first memory bank.