Building the significance layer for AI memory_

DeepaData defines how emotional context becomes a governed, portable record.

The problem

AI captures emotional context it cannot safely govern

No consent model for emotional data — systems infer and retain without structure or permission.
No provenance chain — no way to know where emotional context came from, who authorized it, or how long it should persist.
Emotional understanding trapped in vendor silos — not portable, not auditable, not deletable on request.

Our approach

Governed records for expressed emotional context

EDM — an open standard for structured emotional representation. Published, peer-reviewed, MIT licensed.
.ddna — a governed container with consent, provenance, and retention rules built into every record.
Issue once, verify anywhere, delete on request. Governance travels with the artifact.

Company

DeepaData Pty Ltd

Founded 2025 · Sydney, Australia

The EDM specification is maintained as an open standard at emotionaldatamodel.org

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The open standard for affective context_

EDM captures what most formats miss: not just what was said, but what it meant — as expressed context, not inferred state. It is non-inferential, governance-first, and portable. Published on Zenodo with a DOI and MIT licensed. Implement it yourself, or use our hosted infrastructure.

The standard is open. Build on it freely, self-seal locally, integrate into any memory stack — no DeepaData dependency required. Come to DeepaData when you want a registry entry, a VitaPass address for your user, or a certified artifact that any third party can verify.

Start with 24 fields. Scale to 96. Three profiles for every use case.