Architecture

FactVault as Infrastructure

FactVault is a reliability control plane that sits between your data platform and your AI / decision systems. It does not replace Fabric, Databricks, or Snowflake - it enforces trust boundaries before decisions execute.

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Architecture diagram

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FactVault operates as a minimal moving-parts service: it ingests multi-source records, preserves field-level provenance, and produces versioned outputs with enforceable trust boundaries.

FactVault architecture: sources, data platform, FactVault reliability layer, and AI/decision systems

What FactVault enforces

Trust boundaries (policy)

Decisions should not rely on fields that are low-confidence, externally claimed without approval, or missing provenance. FactVault makes these constraints explicit and enforceable.

Field-level provenance

Every output field retains its source, source field, and reliability — so the chain of evidence remains inspectable, not inferred.

Versioned trust evolution

FactVault versions reliability over time, so organizations can answer: “What did we know, and how reliable was it, when the decision was made?”

Human-in-the-loop governance

When required, decisions can be gated behind approvals. Confirmations and rejections flow back into reliability, triggering recalculation and traceable impact.

If you can’t quantify reliability per field and per source, AI trust stays philosophical. Once you can, many AI trust problems become solvable.

What FactVault is not

FactVault is designed to complement your platform, not replace it.

  • Not a data warehouse — it does not store your full enterprise dataset for analytics.
  • Not an MDM suite — it does not claim to be the “one truth”; it preserves defensible truth.
  • Not a catalog — it does not just document lineage; it enforces reliability at decision time.
  • Not monitoring — it is an infrastructure control plane for decision trust.

Want the precise definition of trust used here? Read What is Data Trust? or download the Data Trust & Reliability Authority Document.

Integration points

FactVault is intentionally minimal and infrastructure-friendly. It typically integrates at three points:

Ingest

Push SourceRecords from systems (CRM, OCR, SharePoint, APIs) into FactVault. Normalize fields at the edge so comparisons remain deterministic.

Enforce

Apply reliability caps, source whitelists, and approval policies. Reliability becomes a first-class, versioned data primitive.

Consume

OutputRecords feed AI systems, reporting, automation, or downstream services — with preserved provenance and enforceable trust boundaries.

Next: What is FactVault? · What is Data Trust? · View the Reliability Report