AI memory
Why can't my AI agent remember what happened?
Because most agents retrieve text. They do not automatically know whether a fact is still true, when it changed, or which source should win when two sources disagree.
The agent repeats stale facts, loses history, or gives a confident answer from an old snippet.
Files and chats contain claims. They are not durable, dated memory.
Give the agent source-backed facts it can query by current state or past date.
"Acme was acquired in 2023."
Acme acquired_by Vertex Labs
Mar 14, 2023 · announcement source
Current owner, past owner, and evidence can be queried separately.
The memory problem
Business facts change constantly. People leave, reporting lines move, customers churn, products launch, and companies get acquired. If an agent only retrieves old text, it can repeat stale facts with confidence because the text still exists.
Example: an acquisition note
A note says Acme was acquired in 2023. That is not enough for an agent to answer safely later.
Why retrieval alone is not enough
Retrieval can find a relevant paragraph. It does not, by itself, decide whether the paragraph is current, whether another source superseded it, or whether the answer depends on a date.
A stale claim can be retrieved just because it matches the question.
The agent may know a claim appeared, but not when it was true.
Two snippets can disagree without a model for which fact supersedes which.
What Oomira gives the agent
Oomira turns trusted sources into dated, cited facts. An agent can ask what is true now, what was true on a past date, and which source supports the answer. That makes memory reviewable instead of purely conversational.
Resolve the current acquired_by fact and show the source.
Resolve the graph before the acquisition date, without rewriting history.