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In Hindsight, a bank is a boundary for agent memories: retain, recall, and reflect work within one bank, and there is no built-in query across banks. The practical choice is whether to pin a client to one bank in its configuration or let application logic select banks at runtime. Choose according to what should be able to remember what—not simply how many users or conversations the application has.
What a Hindsight bank controls
A Hindsight bank defines the scope in which memories can be retained and recalled. Memories in the same bank share that recall space; separate banks do not automatically share memories, and Hindsight does not provide a built-in cross-bank query. The Hindsight field guide’s useful boundary test is: “If A retains a memory, should B be able to recall it?” Hindsight’s field guide to bank strategy recommends separate banks for hard isolation boundaries, such as tenants, customers, or untrusted contexts. Tags within one bank can suit softer categories that sometimes need filtering and sometimes need cross-referencing.
This is a memory-routing choice, not a choice of physical database layout. A bank may be a useful isolation concept, but it should not be treated as synonymous with a database or SaaS tenant database.
How fixed and runtime bank selection differ
Hindsight describes the central distinction as “who owns routing.” In single-bank mode, the bank is specified in the MCP URL or client configuration, so memory operations stay pinned to it. In multi-bank mode, the client connects to the root MCP endpoint and the tool layer can choose, create, or switch banks dynamically; bank-management tools are also available. Hindsight’s comparison of single-bank and multi-bank modes frames the decision as whether the client needs to choose a different bank at runtime.
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| Decision factor | One fixed bank | Multiple selectable banks |
|---|---|---|
| Who routes memory operations | Configuration fixes the bank. | Application or workflow logic selects the bank at runtime. |
| Client complexity | Lower: no per-call bank selection is needed. | Higher: routing rules must consistently map users, projects, or teams to banks. |
| Isolation | More isolated by default in Hindsight’s comparison because the client is pinned to one bank. | Depends on correct runtime mapping; the existence of multiple banks alone does not ensure correct routing. |
| Flexibility | Lower; the client remains in its configured bank. | Higher; the application can select among banks as its workflow requires. |
| Recall sharing | Memories can be recalled within the configured bank; built-in cross-bank querying is unavailable. | Separate banks keep recall separate; selecting multiple banks does not create cross-bank recall. |
| Fragmentation risk | Lower when the configured bank matches the intended sharing boundary. | Higher if IDs are unstable or overly narrow, producing empty or fragmented banks. |
When one bank is the better fit
Use a fixed bank when the client has one stable memory scope and does not need to change it while running. This keeps routing in configuration and reduces the chance that a runtime decision sends an operation to the wrong bank. It is a reasonable starting point when all of the client’s users or work belong in the same recall boundary.
One bank does not mean that every memory must be treated identically. If categories should usually be separated but sometimes cross-referenced, tags can provide a softer partition without creating separate recall boundaries.
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When multiple banks are worth the routing work
Use runtime selection when a workflow genuinely needs different memory scopes—for example, when it must keep tenant, customer, project, or trust contexts apart. The application then takes responsibility for choosing the right bank on each relevant path. That requires an explicit, reliable mapping from context to bank; flexibility without that mapping creates risk rather than useful separation.
Bank IDs also need to be stable and deliberate. Hindsight says banks are created lazily on first use, so a typo or changing ID can create a new, empty bank rather than selecting the intended one. A bank-per-conversation scheme can likewise split a useful history into many small stores. Choose IDs from durable boundaries, and verify that creation and selection behavior matches the intended mapping.
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How to choose the boundary
- Ask the recall question: if one user, agent, project, or context retains a memory, should another be able to recall it?
- Separate hard boundaries: where the answer is no—especially across tenants, customers, or untrusted contexts—use separate banks and make the runtime mapping explicit if the client must choose among them.
- Keep soft categories together: where contexts should sometimes share or cross-reference memories, consider one bank with tags rather than splitting every category into a bank.
- Test the bank identity: confirm that the same intended context resolves to the same stable ID, and that an unexpected ID cannot silently become an empty destination.
- Start with the simplest routing that meets the boundary: Hindsight recommends beginning with a single bank and moving to multi-bank mode when runtime routing needs become real. This is vendor guidance, not a universal rule for every architecture.
How this relates to multitenant databases—and where the analogy stops
The same broad tension appears in multitenant storage: stronger isolation can require more infrastructure and operational work, while shared resources can reduce provisioning overhead but introduce risks such as noisy neighbors and cross-tenant exposure. Microsoft’s Azure Architecture Center notes that storage choices vary in isolation, compliance fit, encryption-key ownership, backup and restore options, geography, operational complexity, migration, and cost. Its guidance is to match the architecture to actual requirements rather than assume one pattern fits all. Microsoft’s overview of storage approaches for multitenant solutions discusses those tradeoffs.
Azure SQL’s SaaS patterns make the comparison concrete: database-per-tenant offers dedicated databases and more granular tenant restore or customization, but increases the work of managing many databases and their schemas. Shared multitenant databases can lower per-tenant cost but require careful tenant identification and query scoping; Microsoft flags cross-tenant exposure and noisy-neighbor risks. Sharding adds a tenant-to-database catalog and processes for moving, splitting, or merging shards. Microsoft’s Azure SQL SaaS tenancy patterns cover these options.
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That is an analogy, not an equivalence. Hindsight bank selection controls memory recall scope and routing. Database tenancy controls data placement and operational isolation. The shared lesson is to pay for complexity where a real isolation or operational requirement calls for it, rather than assuming either maximal sharing or maximal separation is always right.
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