Fabric IQ in Riyadh
Fabric IQ is the context layer that models your business as an ontology — entities, relationships and measures that both people and AI agents reason over as one shared meaning. We build that layer on a unified OneLake foundation, because an agent is only as good as the context it reasons from.
Fabric IQ is Microsoft's context layer — an ontology that models how your business actually operates, so people and AI agents reason over the same shared meaning. It only works on a unified data foundation, which is where most estates are not yet ready. Saudi organisations are running SAP S/4HANA migrations at scale — driven by ZATCA e-invoicing requirements and Vision 2030 digitalisation mandates. The S/4 implementation creates a data foundation that most organisations haven't yet built an analytics layer on top of. There is a significant gap between the ERP investment and the analytics capability in most Saudi private sector companies — and a growing recognition, at CEO and CFO level, that the gap needs to close.
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Get started with Fabric IQ — Riyadh
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What we hear from operators
The problems we solve
These aren't hypothetical pain points assembled from industry reports. They're observations from actual plant floors, warehouse ops, and finance desks — written down because they come up in almost every first conversation.
Agents reason from raw tables, not business meaning
Point an AI agent at raw Fabric tables and it has to guess how your business fits together — which table is the order, which field is the customer, how a plant rolls up to a region. Without a modelled ontology it guesses, and it guesses inconsistently. Fabric IQ is the layer that gives the agent your actual business meaning to reason from.
Every team defines the same metric differently
Finance, operations and supply chain each have their own definition of OEE, OTIF or margin, so an agent asked the same question by two people can return two answers. A shared ontology forces one definition of each entity and measure, which is the prerequisite for agents — and people — to agree on the number.
The data is not unified, so there is no context to model
An ontology models relationships across your business, which needs the data in one place to relate. If your sources have not met in OneLake, there is nothing coherent for Fabric IQ to sit on top of. Unify first; model the context second. The order is not optional.
Agentic ambition with no governed foundation
Leadership wants autonomous agents acting on operations. Built on a fragmented, ungoverned estate, those agents act confidently on wrong context — which is a bigger risk than the manual process they replace. Fabric IQ plus a governed foundation is what makes agentic operations safe enough to run.
How we work
Our approach
01
Unify the data in OneLake
Fabric IQ reasons over a single foundation, so we connect the sources — SAP, MES, WMS, CRM — into a governed OneLake estate first. This is the unglamorous prerequisite that decides whether everything above it is trustworthy. No context layer rescues fragmented data.
02
Model the ontology
We model your business as entities, relationships and measures — what an order is, how it relates to a customer and a plant, how OEE and OTIF are defined once for everyone. This is the shared context that Fabric IQ exposes to people and agents alike, and getting the definitions right with the business owners is the real work.
03
Connect agents and operations
With the ontology in place, we connect the operational loop — agents that observe live signals, reason over the shared context, and take governed action with human approval on anything consequential, surfaced where people already work in analytics, operations and Copilot. This is where a modelled business becomes an operating one.
What changes
Outcomes
These are specific, measurable shifts — not benefit statements. Every outcome listed here has been achieved with a client.
One definition of each entity and measure across the business
OEE, OTIF and margin mean the same thing to finance, operations and every agent, so answers agree instead of contradicting.
Agent accuracy: reasoning from business meaning, not guessed table joins
Agents ground on the ontology rather than inferring structure from raw tables, so their reasoning follows how the business actually works.
Governed action in the moment, with human approval where it matters
The operational loop lets agents act on live signals within guardrails, keeping a person in control of anything that spends money or touches a customer.
Reuse across analytics, operations and Copilot
The same modelled context serves dashboards, operational agents and Microsoft 365 Copilot, so the investment compounds rather than being rebuilt per tool.
Technology stack
Common questions
What buyers ask us
These are questions that come up in almost every first or second conversation. If yours isn't here, it will be in the first call.
What is Microsoft Fabric IQ?
Fabric IQ is Microsoft's enterprise context layer — an ontology that models how your business operates so that both people and AI agents reason over the same shared meaning. It sits on top of your Fabric data and turns a data platform into an intelligence platform that agents can reason against. It is part of the wider Microsoft IQ family alongside Work IQ, Foundry IQ and Web IQ.
Is Fabric IQ generally available?
Yes. Microsoft first announced Fabric IQ at Ignite in November 2025 and made it generally available at Build in 2026, alongside the general availability of Operations Agents and Graph. The Ontology layer that grounds agents in business meaning continues to expand with further capabilities and integrations across Fabric, Foundry and Microsoft 365 Copilot.
How does Fabric IQ relate to a Fabric Data Agent?
Fabric IQ is the shared context — the ontology — and a Fabric Data Agent is one of the things that reasons over it. An agent grounded on a modelled ontology answers with your business meaning rather than guessing structure from raw tables, which makes it far more reliable. You can build data agents without Fabric IQ, but the ontology is what lets multiple agents and people agree on the same definitions.
Do we actually need Fabric IQ, or are dashboards enough?
If your goal is reports people read, a governed semantic model and Power BI may be enough. Fabric IQ earns its place when you want AI agents to reason and act over your operations, because agents need modelled business context to be trustworthy at that job. It is the foundation for agentic operations, not a reporting upgrade — so the honest answer depends on whether agents acting on your data is where you are heading.
What is an ontology in this context?
An ontology is a model of your business in terms of entities (order, customer, plant, shipment), the relationships between them, and the measures that describe them (OEE, OTIF, margin) — defined once, consistently. It is the difference between an agent seeing a pile of tables and an agent understanding that this order belongs to this customer and was made at this plant. Building it well is a business exercise as much as a technical one, because the definitions have to be owned by the business.
What are the prerequisites before we start with Fabric IQ?
A unified data foundation in OneLake and a governed semantic model. Fabric IQ reasons over a single coherent estate, so if your sources have not met and your definitions still fork by team, that is the work to do first. We often sequence it as: unify the data, govern the model, then build the ontology — trying to model context over fragmented data produces a confident but wrong intelligence layer.
Further Reading
Practitioner insights on this topic
Power BI Consulting in Riyadh for Manufacturing Companies: What the Work Involves
A group operations director has three numbers for last month's output — the plant manager's Excel, a Power BI report from the ERP team, and finance — and they disagree. Power BI isn't missing; it's everywhere, each report encoding a private definition. What a Riyadh consulting engagement actually fixes.
Read article →
Microsoft FabricBest Microsoft Fabric Consulting Partners in UAE and GCC: How to Choose
A Fabric proposal from a strong partner and one from a weak partner look almost identical. No independent body audits delivery quality here, so any ranking is paid placement or directory badges. A buyer's criteria guide — provider types, a scoring matrix, and the questions that separate capable from confident.
Read article →
LeadershipFractional CDO vs Fractional Data Consultant: Where GCC Companies Draw the Line
ERP is live, and then the chairman asks why consolidated margin by customer differs from the sales director's number — and the answer takes nine days. Two very different fixes get proposed to that problem, and they are routinely confused. How to tell which you actually need.
Read article →
Other markets
Fabric IQ in other markets
The operational problem rarely changes at the border. The ERP estate, the compliance regime and the reporting cycle do.
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Start with a conversation, not a proposal
First call is 30 minutes with Amit. We ask about your systems, your team, and your most pressing operational problem. You get a clear view of where the gap is and what closing it looks like. No slides. No pitch deck. No obligation to proceed.