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Trusted Analytics V1 adds an enforcement layer between the agent and your data.

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Core idea

V1 closes the trust gap with three guarantees:
  1. Scope — only approved tables and joins
  2. Meaning — governed metric definitions
  3. Safety — policy-enforced execution (PII, limits, time filters)

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V1 building blocks

LayerPurposePrimary files
Semantic modelDeterministic metrics and joinssemantics/semantic_model.yml
Business rulesGuidance and domain constraintssemantics/business_rules.yml
Dataset bundlesAllowed tables + join graphdatasets/<bundle_id>/dataset.yaml
PolicyEnforceable constraintspolicies/policy.yml
Execution contractsPer-query audit artifactcontracts/runs/*.json

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Runtime flow

  1. User asks a question.
  2. Agent calls build_contract.
  3. Policy engine returns allow, block, or needs_clarification.
  4. If allowed, execution runs with contract_id.
  5. Contract is persisted for provenance.

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Strict vs compatibility mode

policies/policy.yml controls runtime strictness: 
execution:
  require_contract: false
  • false: backward-compatible behavior
  • true: strict contract gating (recommended for production)

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Why V1 matters

  • Consistent revenue-style metrics across LLMs
  • Deterministic PII blocking
  • Query boundary control with dataset bundles
  • Auditable artifacts for compliance and debugging

Validation and testing

Run dazense validate, dazense eval, and dazense eval --engine