Fabric Semantic Intelligence

Make your data agent-ready with Fabric IQ

Agents are only as accurate as the context they reason over. We turn your Power BI semantic models and business definitions into a governed Fabric IQ ontology, prove the accuracy gain in a fixed-price sprint, then take it to production.

Book a One-Day Benchmark See services

FABRIC IQ IN COPILOT

Business context now grounds Microsoft 365 Copilot

Fabric IQ brings semantic model context into Copilot. The quality of that context decides the quality of the answers.

ONE ONTOLOGY, MANY AGENTS

Six ways to use one governed model

The same ontology serves data agents, operations agents, Foundry and Copilot Studio agents, and any MCP client.

TIMING

Moving to the new Ontology experience

If you built on the earlier Ontology experience, we move it to the new one and pair that move with a context build.

The semantic stack

Your existing Power BI investment is the starting point

Each layer builds on the one below. We build the ontology on top of what you already own, and connect it to the agents your people use.

Agents and CopilotData agents, operations agents, Microsoft 365 Copilot, agentic apps

Uses context

Fabric IQ OntologyBusiness entities, relationships, rules and metrics as one governed model

Where we build

Fabric IQ context layerOneLake, semantic models, ontology and real-time data combined

Grounds Copilot

Power BI semantic modelsCertified measures, security and relationships you already own

Your starting point

OneLake and EventhouseLakehouses, warehouses, mirrored and streaming data

Data foundation

Agent integration

Six ways your agents use one ontology

Ontology agentAuthor, test and improve the ontology in plan and act modes

Fabric data agentConversational answers over governed Fabric data

Operations agentReal-time monitoring against business rules, with Teams alerts

Foundry IQ agentCustom agents in Microsoft Foundry with tool calling

Copilot Studio agentLow-code agents grounded in the ontology

Any MCP clientBring your approved model through the ontology MCP endpoint

If your policies limit which AI models you can use, the MCP endpoint lets your approved model query the governed ontology with your identity and security intact.

Services

Fixed-scope services, each with a clear next step

Prove value fast

Context Lab Sprint

Before and after proof of agent accuracy on synthetic domain data, ending in a scoped production plan. Best when an AI pilot has stalled.

Semantic ClarityOne source, accuracy baseline

Connected DataOntology and agent

Audit-ReadyPurview and MCP endpoint

For: CDO, Head of AI

Agent Pilot Diagnostic

A structured review of a stalled GenAI pilot: context gaps, ontology audit and query traces, with a root cause and a fix path.

For: CTO, CDO

One-Day Benchmark

Your own questions run against your current AI and a context-enriched version, scored on accuracy and consistency.

For: Data and analytics leaders

Copilot Remediation Sprint

A semantic layer under Microsoft 365 Copilot and Copilot Studio, aimed at the question types users stopped trusting.

For: Microsoft 365 owner, CDO

Built on what your experts know

Regulatory Reasoning Agent

Agents that show the ontology path and rules behind each answer, with lineage and agent identity for audit. Built for programs such as DORA, BCBS 239 and SR 11-7.

For: CRO, compliance, risk

Synthetic Domain Data Lab

Domain-faithful synthetic data so a pilot can run and be measured without touching production records.

For: CDO, data protection

Domain Vocabulary Sprint

Working sessions with your senior analysts that turn their knowledge into governed entities, rules and metrics.

For: Head of analytics, COO

Shadow AI Consolidation

An audit of every Copilot and chatbot deployment, consolidated onto one governed context layer so answers agree.

For: CIO, CISO

Agents that scale

Well-Architected Agent Review

A scored review across accuracy, safety, observability, reliability, governance and cost, with a prioritized fix list.

For: Enterprise architects

Multi-Agent Architecture Sprint

Agent topology, tool registry, handoff contracts and token budgets designed before agent sprawl sets in.

For: Enterprise architects

API-to-Agent Conversion

Your existing APIs exposed as governed MCP tools, with business meaning from the semantic layer.

For: CTO, platform engineering

Ways to buy

Context Layer as a Service

A maintained, versioned domain context layer with agreed coverage and accuracy reporting.

For: CDO, finance

Semantic Model Conversion

Years of Power BI semantic models converted into an agent-ready ontology, so you start from what you already have.

For: Head of BI, CDO

Azure Co-Funding Plan

Each proposal shows list price, eligible Microsoft funding and Azure commitment applied, and your net cost.

For: CFO, procurement

Engagement and investment

Every engagement ends at a decision, not a document

You see evidence at each step, then decide whether to go further. Figures are typical ranges in USD before any Microsoft funding; your proposal follows a short discovery call.

PHASE 1

Context Lab Sprint

Fixed price, synthetic data, before and after evidence

2 to 4 weeks
$20K to $55KDecision: is the accuracy gain real?

PHASE 2

Context build

Production ontology, data agent, Copilot or MCP integration, governance baseline

4 to 8 weeks
$60K to $120KDecision: do users accept the agent?

PHASE 3

Expand

Second domain, operations agents, multi-agent design

3 to 6 weeks per workstream
$30K to $80K per workstreamDecision: where next?

PHASE 4

Run

Managed context layer, versioning, accuracy benchmarking, quarterly review

Monthly
$8K to $20K per monthOngoing improvement

Domains

Domain context libraries we build once and reuse

Financial services and insurance

Regulatory reporting, liquidity and credit risk, policy and claims, finance close

Manufacturing and high-tech

Asset hierarchies, maintenance and work orders, OEE, quality, supply chain

Life sciences and healthcare

Quality management, clinical and commercial entities, trial data

Energy and utilities

Grid assets, outages, consumption forecasting, emissions reporting

Where to start

Sound familiar?

Copilot users stopped trusting answersCopilot Remediation Sprint →

An AI pilot gave inconsistent resultsAgent Pilot Diagnostic →

You have 100+ Power BI semantic modelsSemantic Model Conversion →

You built on the earlier Ontology experienceContext Lab Sprint →

Your data is too sensitive for a live pilotSynthetic Domain Data Lab →

You run DORA, BCBS 239 or SR 11-7 programsRegulatory Reasoning Agent →

You have several agents and no shared designMulti-Agent Architecture Sprint →

Snowflake and Fabric run side by sideCross-platform semantic advisory →

Recognition

Recognized for data and AI excellence

MSMicrosoft

Microsoft Fabric Featured Partner

Recognized for delivering customer solutions on Microsoft Fabric.

CIOCIO Times

The Fastest-Growing Analytics & AI Companies Driving Business in 2026

Named among the analytics and AI companies driving business growth.

2026

AIMAIM

Best Firm for FDE Talent

Recognized for forward deployed engineering talent.

2026

AIMAIM

Minsky Award for Excellence in AI Strategy Consulting

Recognized for AI strategy consulting.

2026

Start with proof

Book a One-Day Benchmark or a Context Lab Sprint

Bring the questions your users ask. We show the accuracy difference governed context makes before you commit to anything larger.

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