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Works with your AI tools

MCP-compatible out of the box

Why enterprise AI initiatives stall

No shared metric definitions

Your BI tool says revenue is $4.2M. Your AI says $3.9M. Both are technically correct but they're using different business logic. Every tool defines metrics independently, and AI tools inherit the inconsistency.

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AI that confidently returns the wrong answer

When AI tools query raw warehouse data, there's no guarantee the numbers are right, current, or correctly scoped. Hallucination isn't just a model problem, it's a data problem. AI tools without a governed data layer will get things wrong, and they'll sound certain doing it.

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No governed access layer for AI

AI tools can query anything in your warehouse including data they shouldn't touch. There's no layer that enforces who can ask what, or ensures sensitive data stays protected when AI is in the loop.

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Data that isn't modeled for AI consumption

AI projects stall waiting for clean, modeled data. Engineering backlogs grow. Analysts rebuild the same schemas in every tool. The semantic foundation AI tools need never gets built.

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See what a governed AI data layer looks like in practice.

How Mosaic gives AI agents a governed data foundation

Mosaic is a semantic layer that sits between your data warehouse and the tools that consume it. It doesn't move your data. It defines how your data gets interpreted, who can access it, and how fast it gets served.

One metric definition. Every tool.

Define revenue, churn, CAC, or any business metric once in Mosaic. Every BI dashboard, AI agent, and analyst query resolves to the same number — because they're all reading from the same semantic model.

MCP Integration: Mosaic exposes your semantic layer to AI tools via the Model Context Protocol — so Claude, Copilot, and any MCP-compatible tool reasons over governed business definitions, not raw SQL. And because the semantic layer is the constant, you can swap LLMs without re-modeling your data or reconciling your metrics.

AI safety and governed access, built in

Mosaic Sentinel is your AI safety layer. Define exactly which datasets AI tools can reach including hard boundaries around PII and sensitive data. Sentinel tracks every query made through the semantic layer, by humans and AI agents alike, giving you a full audit trail for compliance without rebuilding your warehouse access controls. And because agents only ever see clean, scoped, governed data, you eliminate a root cause of hallucination at the source.

A governed semantic model in 30 minutes

Schema creation that used to take a day now takes 30 minutes. Connect a data source, describe what you're modeling, and Mosaic Studio generates the joins, attributes, and relationships that’s ready for AI tools to query immediately.

What a governed AI data layer looks like in production

What does this look like when it's running?

AI Agents Grounded in Logic

Connect Claude, Copilot, or any MCP-compatible agent to your Mosaic semantic layer. LLMs answer questions using your actual business definitions, not whatever the raw SQL happens to return.

Consistent Metrics Across Every Tool

Power BI, Tableau, and Looker all resolve to the same revenue and KPI definitions. No more reconciliation meetings when numbers don't match across dashboards.

Build AI apps on trusted data — without a data engineering dependency

AI teams can build and ship applications grounded in governed business data without waiting on engineering to model it first. Connect a source, generate the semantic model in Mosaic Studio, and start building — your app is querying real, consistent business logic from day one.

Data Governance & AI Observability

Define exactly which datasets AI tools and analysts can access. Mosaic Sentinel logs every query for compliance without touching your existing warehouse security model.

"We believe Strategy AI will have a significant impact at Bayer by giving our users automated, conversational insights about our critical data."

- Mathew Ratnam Director and Digital Lead, Data & Analytics · Bayer

White Paper: Implementing Enterprise AI at Scale

Mosaic exposes your semantic layer to AI agents via the Model Context Protocol. To see how this standardizes communication between your warehouse and LLMs like Claude or Copilot, download our whitepaper.

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Frequently Asked Questions

What is a semantic layer for AI agents?

A semantic layer is a data modeling layer that sits between your warehouse and the tools querying it. For AI agents, it means the agent doesn't query raw tables — it queries governed, pre-defined business metrics. Mosaic is a semantic layer that exposes those definitions to AI agents via MCP, so agents always work from consistent, access-controlled business logic.

What is Model Context Protocol (MCP) and why does it matter for enterprise data?

MCP (Model Context Protocol) is an open standard that lets AI agents communicate with external data sources and tools in a structured way. For enterprise data, MCP matters because it gives AI agents like Claude or Copilot a governed interface into your data instead of writing raw SQL or accessing warehouse tables directly. Mosaic exposes your semantic layer via MCP, so AI agents reason over business definitions, not raw data.

How is a semantic layer different from a data warehouse or data lakehouse?

A data warehouse stores and organizes your raw data. A data lakehouse adds flexibility for unstructured data on top of that. Neither tells your tools what the data means. A semantic layer like Mosaic sits on top of your existing infrastructure and defines the business logic, what "revenue" means, who can access it, how it's calculated, without moving or copying your data. Your warehouse stays the source. Mosaic becomes the interpretation layer every tool reads from.

How does Mosaic handle AI governance and data access controls?

Mosaic Sentinel tracks every query made through the semantic layer by humans and AI agents alike. You define which datasets each AI agent or user role can access, and Sentinel logs every query for compliance audit trails. This happens at the semantic layer, so you don't need to modify your warehouse access controls.

Strategy Mosaic: See your data, unified.

Book a 30-minute demo with our team. We'll show you how to connect Mosaic to your existing tools and get AI agents reasoning over governed business data starting with your actual data model.

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Connect Any AI to Your Governed Data with MCP and Mosaic