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ODI / ODIP

Operational Decision Intelligence (ODI) and the ODIP platform model — the definitions and reference model we use to build Veratix Compass.

Operational Decision Intelligence

Operational Decision Intelligence (ODI) is the discipline of transforming operational reality into explainable signals and governed actions, with traceable, auditable outcomes that drive continuous improvement. ODIP is the platform model that makes ODI repeatable across teams, tenants, and systems.

Glossary•Downloads•Versioning
Status
Draft (public-facing)
Scope note

This page governs language and conceptual models. It does not disclose internal algorithms, training data, or implementation secrets.

Why ODI exists

Modern operational systems generate vast amounts of data, yet operational decisions remain fragmented, ad-hoc, and difficult to defend. ODI exists to answer the questions operations teams are accountable for.

  • What happened? Facts and event history
  • What does it mean? Context, ownership, baselines, policy
  • What should we do? Recommended or automated actions
  • Why is this correct? Evidence that withstands scrutiny

ODI → ODIP reference model

Veratix formalizes ODI as a layered model so teams can reason about correctness, trust, and outcomes without confusing “data storage” with “intelligence.”

  1. Trust & Governance — tenancy, RBAC, audit, retention, policy, versioned meaning
  2. Ingestion — stable event envelopes, schema evolution, tenant-scoped pipelines
  3. Context — ownership graphs, baselines, constraints, classifications, references
  4. Signal — explainable detections packaged with evidence
  5. Action — workflows, routing, enforcement, automation
  6. Learning — outcomes, feedback loops, drift management

Reference visuals

These diagrams are part of the ODI/ODIP definition set and are versioned alongside the text.

ODI Intelligence Loop
ODI intelligence loop — observe → contextualize → signal → act → learn.
ODI vs Analytics
ODI vs analytics — decision-and-action oriented, governed by trust and policy.
Signal anatomy
Signal anatomy — evidence + context + logic → explainable output.

Key principles

  • Context before signals — ownership, baselines, and constraints come first.
  • Governance before automation — actions must be auditable and controlled.
  • Evidence over confidence scores — prefer explainable evidence trails.
  • Meaning as infrastructure — definitions are versioned and treated as part of the trust layer.