Duodata — Business-Approved Metrics for AI, semantic layers, and data platforms.

The Business-Approved Metrics and Metrics Ontology

Duodata is where business and data teams agree on what a metric means, then push that definition into AI assistants, Snowflake, Databricks, Microsoft Fabric, and BI tools. Talk to your data and get one answer everywhere.

Talk to us about your metrics problem

Metrics chaos is slowing every decision.

Without a Metrics Ontology and an approved definition layer, the same KPI means different things in AI tools, data platforms, semantic layers, and dashboards.

• AI answers without approved context. When users talk to your data through Copilot, ChatGPT, or custom agents, the tools make up metric logic. Answers erode trust in AI and contradict the dashboard.
• KPI disputes in every meeting. Finance, sales, and product show different numbers for the same KPI. QBRs and board reviews stall while teams reconcile live.
• Manual reconciliation consumes analyst capacity. Data teams spend roughly 30% of their time reconciling definition drift instead of analyzing. Spreadsheets cannot keep pace with enterprise reporting.

"Organizations that prioritize semantics in AI-ready data will increase their agentic AI accuracy by up to 80% and reduce costs by up to 60% by 2027." — Gartner, 2026

What Duodata does

A Business-Approved Metrics layer and Metrics Ontology that defines metric logic once, governs it centrally, and projects it into your entire data stack.

Capture and govern metric definitions

• Define metrics, slices, reports, and sources in business language.
• Keep ownership, status, and approvals in one place.

Deploy consistent logic into your stack

• Project metric definitions into AI and BI tools, Snowflake, and Databricks.
• Avoid drift when new AI agents or dashboards are added.

Document and explain every metric

• Auto-generate human- and agent-friendly documentation and value driver trees.
• Show how metrics relate and where they are used.

How Duodata fits into your metrics workflow

Duodata introduces new capabilities across the entire metrics lifecycle — from discovery to secure deployment.

1. Discover — AI scans docs, SQL, and tools to surface existing metrics.
2. Manage — Build your Metrics Ontology: one business-approved source of truth for metric definitions.
3. Document — Auto-generate, version-control, and share metric documentation.
4. Integrate — Connect Snowflake, Databricks, semantic layers, BI tools, and AI agents.
5. Deploy — Publish into Snowflake Semantic Views, Databricks Metric Views, and Microsoft Fabric semantic models.
6. Secure — Apply SOC 2–ready controls, SSO, and RBAC to your metrics layer.