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🎛️ FAQ

What teams usually ask first

What does Fabric actually build?

Fabric builds production AI systems for operational companies. That can include one high-value workflow if there is already an idea being discussed by executives. Fabric Signal OS provides a reusable context layer your business can query and run reliable agents on, so bottlenecks and opportunities can be identified earlier and better opportunities can be serviced across the business.

Do we need a perfect data warehouse before starting?

No. A clean warehouse helps, but it is not the only starting point. Fabric looks at the systems, documents, dashboards, workflows, and expert knowledge the company already relies on, then identifies which signals are ready, which gaps matter, and where a practical first system can create value.

How does your intelligence assessment relate to Signal OS?

The audit maps how your business really works: metrics, source systems, permissions, exceptions, and the knowledge that lives with key people. Signal OS turns that mapped context into a governed answer layer that teams and future agents can query with confidence.

Is Fabric only for analytics questions?

No. Trusted answers are often the first visible use case, but the bigger goal is operational leverage. Fabric can support reporting, estimate review, project risk, margin leakage, customer follow-up, workflow automation, and agentic systems that need reliable business context before they act.

How do you keep AI outputs trustworthy?

We ground systems in approved data sources, business definitions, user permissions, and reviewable logic. Admins and subject-matter experts help define how answers should work, while end users get clarity without being able to silently change the rules underneath the system.

Who is Fabric built for?

Fabric is built for operational businesses where work is complex, concrete, and full of local knowledge, including construction, field service, logistics, manufacturing, distribution, and the back-office teams that keep those businesses moving.