The cognitive memory layer for AI.
Inspired by neuroscience
What is ImMemora
A cognitive memory layer that models facts, reasoning, and decisions as memory units with state and relations. It also preserves the why behind choices for explainable, contextual recall.
How it works
Each input is decomposed into entities, events, evidence, and hypotheses; normalized into a semantic graph and indexed to vectors. A neuro-inspired multi-factor scoring handles priority, novelty, trust, and conflicts, with a memory lifecycle.
What it is for
Reconstructs contexts and decision rationales in domains with high complexity or responsibility (e.g., forensic, clinical, enterprise). Reduces ambiguity, maintains a verifiable history, and enables answers with traceability of the why.
The cognitive memory layer
ImMemora turns conversations and documents into a connected memory: it captures, unifies, and weighs useful signals to deliver explainable, contextual answers. Every recall reinforces the memory, which improves over time.
How ImMemora works
Capture
Extracts the signals that really matter from conversations, documents, and tools.
Unify
Deduplicates and links everything into a persistent memory made of vectors and graph.
Weigh
Assigns dynamic importance with a multi-factor scoring (priority, trust, novelty, conflicts).
Retrieve
Finds the best evidence (top-N) with strong deduplication and conflict handling.
Explain
Answers by showing the path on the graph and the sources used.
Reinforce
Updates frequency and timestamps at every recall — the memory gets better over time.