Definition · AI in finance
Agent memory
Agent memory is information an AI agent stores or retrieves across steps or sessions so it can maintain context while working toward a goal. For agent memory, the useful boundary is the data, tools, approvals, human review, evaluation standard, and decision the system may influence.
Also known as AI agent memory, long-term memory
Why it matters
Understanding agent memory matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo grounds each run in a connected, live system of record rather than relying on agent memory, so analysis reflects current data, not stale recollection.
In practice
Governance example
Teams use agent memory when they evaluate whether an AI-assisted analysis can be trusted. The useful test is whether the output is tied to approved data, repeatable logic, human review, and an audit trail.
Pluvo example
Pluvo grounds each run in a connected, live system of record rather than relying on agent memory, so analysis reflects current data, not stale recollection.
In practice, teams should define agent memory with a clear source, owner, time period, and decision before they use it in reporting, planning, or operating reviews.
Understanding agent memory matters because AI-assisted finance work can sound confident even when data, assumptions, or compute paths are wrong. A useful definition keeps the output grounded, reviewable, and accountable. Pluvo grounds each run in a connected, live system of record rather than relying on agent memory, so analysis reflects current data, not stale recollection.
A strong workflow for agent memory separates the definition from the action: first agree what the term means, then decide how it is measured, when it changes, and who is accountable for the next step.
Pluvo grounds each run in a connected, live system of record rather than relying on agent memory, so analysis reflects current data, not stale recollection.
FAQ
What is agent memory in AI?
Agent memory is information an AI agent stores or retrieves across steps or sessions so it can maintain context while working toward a goal. For agent memory, the useful boundary is the data, tools, approvals, human review, evaluation standard, and decision the system may influence.
How do AI agents remember past context?
To use agent memory, start with the decision, then confirm the source data, timing, calculation logic, and owner. The analysis is strongest when a reviewer can trace the answer back to the records that produced it.