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Hindsight’s own engineering guidance (Ben Bartholomew, Hindsight Team, July 16, 2026) puts it in one line: “A bank is a recall boundary.” This article covers how to draw that boundary, how to combine private, shared and global memory, and which ingestion details matter once you retain real customer conversations.
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How Hindsight’s memory flow works
Hindsight exposes three core operations, described in its Main Methods guide and the Retain documentation:
- Retain ingests content and extracts structured facts, entities and connections. The stored memory is that structured representation, not the verbatim original. A conversation can be sent as a single item with clear speaker and time attribution.
- Recall searches one specified bank for relevant memories. The Cloud recall API describes semantic similarity plus spreading activation. The developer guide adds controls for result budget, memory type and source chunks.
- Reflect reasons over memories and observations to generate a response. It applies the bank’s disposition and uses an LLM. Its examples can return the supporting facts alongside the answer.
Each operation works inside one bank. Per the July 2026 guide, there is no built-in query that spans banks. That single property is what makes banks usable as a privacy boundary, and it is why the rest of the design is about choosing which bank(s) a given request may address.
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Bank or tag: which one should be the customer boundary?
A bank is a recall boundary. A tag is a filter passed along with a call. They enforce separation at different points, and that difference decides which one can carry a customer-privacy requirement.
| Question | Separate bank | Tags in a shared bank |
|---|---|---|
| Where is separation enforced? | At the storage and recall boundary: an operation addresses one bank. | At request time, by the tag filter supplied with each recall. |
| What if the application forgets something? | A wrong bank ID is the failure mode, so authorize every ID. | An omitted or mis-built filter can return other customers’ memories. |
| Best use | Customer, tenant or user isolation. | Soft partitions: source, project, channel, topic, sensitivity. |
| Cross-scope reuse | Application-side fan-out across authorized banks. | One recall call with a broader or narrower filter. |
Hindsight’s guidance recommends a distinct bank for a hard isolation boundary such as a tenant or customer. It also warns against the opposite extreme: one bank per conversation fragments recall, because every new bank starts with no prior memories. The right granularity is the customer or user, not the session.
Why tags are not the customer privacy wall
The retain documentation describes tags as visibility scoping: a memory comes back in recall when its tags match the tag filter on the request. Suggested conventions include user:<id>, session:<id>, room:<id> and topic:<name>. These work well for organization.
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This is Hindsight’s architectural recommendation, not a claim that tag filtering can never be made safe with additional controls. If cross-customer recall would be a serious incident for your product, put the customer in the bank choice and keep tags for finer distinctions inside it.
Choosing scopes: private, shared and global memory
“Customer-specific” can mean different things in a B2B product. Decide explicitly which memories are visible to whom, then give each class its own bank.
| Scope | Bank granularity | Use when |
|---|---|---|
| Private user memory | One bank per user | One user’s interactions must not appear to another, even in the same company. |
| Shared account memory | One bank per organization | Every seat is meant to share organization facts, such as plan details, preferences or ongoing issues. |
| Global product knowledge | One shared bank, generally read-mostly | Common documentation or defaults that apply to everyone. |
Writes need the most care. A fact belongs in the organization bank only when it is genuinely meant to be shared with every seat. A user’s private remark about a colleague belongs in that user’s bank. These scopes are design choices in your authorization model; Hindsight does not decide them for you.
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Because no query spans banks, composition happens in your code. The August 4, 2026 guide describes a fan-out pattern: query each bank the current caller is entitled to access, then merge and rank the results in the application.
For a support agent, that might mean recalling from the user’s bank, the user’s organization bank and the global product bank, then combining the results before building the prompt. The entitlement list is the important part. It should come from the authenticated session, never from client-supplied input.
The request loop, step by step
The documented APIs suggest this loop. It is an implementation pattern assembled from those APIs, not behavior Hindsight performs for you: Hindsight does not authorize your users.
- Authenticate the caller with your normal identity layer.
- Map the caller to permitted banks on the server, for example the user’s own bank, their organization’s bank and the global bank. Derive these IDs from authenticated identity, not from a field the client can set.
- Recall from each permitted bank and merge and rank the results in application code. Add tag filters only for optional narrowing, such as one product area.
- Build the prompt from the returned context and generate the answer. If you use reflect instead, call it against a bank you have already authorized.
- Retain the new interaction into exactly the bank where it belongs: private details to the user bank, genuinely shared facts to the organization bank.
A minimal sketch of the authorization step, in pseudocode rather than a specific client library:
def banks_for(session):
# IDs come from the verified session, never from the request body
return {
"private": f"user_{session.user_id}",
"shared": f"org_{session.org_id}",
"global": "product_knowledge",
}The naming convention above is only an example. What matters is that IDs are derived deterministically from authenticated identifiers.
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Keep bank IDs stable and server-controlled
Hindsight’s engineering guide notes that banks are created lazily. A typo, a changed ID format or a renamed customer can silently address a new, empty bank instead of failing. The agent then appears to have forgotten everything, with no error to tell you why.
- Base IDs on immutable internal identifiers, not on display names, email addresses or company names that can change.
- Generate IDs through one shared function so reads and writes cannot drift apart.
- Never accept an arbitrary bank ID from an untrusted request body. Bank selection controls which isolated memory an operation can reach, so it is an authorization decision.
Hindsight’s Memory Banks documentation covers bank configuration in more detail.
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The retain API accepts content plus optional metadata: context, timestamp, document ID, tags and observation scopes.
Context
Context is injected into the extraction prompt, so a label such as “support ticket” helps the extractor interpret what a statement means. Use it to distinguish, say, a customer complaint from a sales call or an internal note.
Timestamps
An ISO 8601 timestamp anchors relative expressions such as “next Tuesday” or “last month”. Pass the real event time when you know it, rather than silently treating ingestion time as event time. The special value unset is for timeless reference content, such as policy documents.
Document ID and updating growing conversations
When a conversation grows, you can retain the full updated content again with the same document_id. Hindsight deletes the previous version and reprocesses from scratch. That makes updates idempotent, but it is replacement, not an append-only log. Choose one stable document ID per logical conversation and always send the complete updated transcript. Sending only the newest messages under the same ID would replace the earlier ones.
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Tags
Inside a customer’s bank, tags are the right tool for distinctions you may want to filter on later: topic:billing, channel:email, project:migration. They refine recall; they do not replace the bank boundary.
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Observation scopes
Observation scopes control how retained facts contribute to consolidated observations. The documentation distinguishes three modes:
- Combined scope: useful when a memory only makes sense with all of its associated tags together.
- Shared untagged scope: a global summary view that is not split by tag.
- Per-tag scope: per-tag passes create independently scoped observations.
Pick the mode from the questions your agent needs to answer. Do not assume every cross-tag combination already has a prepared observation.
What the published benchmarks do and do not tell you
The paper Hindsight is 20/20: Building Agent Memory that Retains, Recalls, and Reflects (arXiv preprint, December 2025) describes four logical memory networks covering world facts, agent experiences, synthesized entity summaries and evolving beliefs. Its authors report:
- 83.6% overall accuracy with an open-source 20B model, versus 39% for a full-context baseline using the same backbone.
- 91.4% on LongMemEval with a larger backbone.
- Up to 89.61% on LoCoMo, versus 75.78% for the strongest prior open system.
These are the authors’ own results under their evaluation settings. They indicate that structured memory is worth evaluating, but they are not a guarantee for a deployed support product and not a test of customer isolation. For integration behavior, rely on the official bank and API documentation, which is the more current source.
The Bottom Line
Make the bank your customer boundary, derive bank IDs from authenticated identity, and write each memory to exactly one scope. Treat tags as a convenience for narrowing recall, not as the control that keeps one customer’s data away from another.
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