GoodData ushers in era of governed & trustworthy AI analytics

Artificial intelligence (AI) analytics and data intelligence firm GoodData announced the launch of Intelligence Layer, a suite of governed, context-aware AI capabilities that bridge the gap between raw data and trustworthy, action-ready intelligence.

Designed for organizations working in complex data environments, either on-premises or across multiple clouds, Intelligence Layer ensures that AI operates according to the company’s own rules, logic, and semantic definitions, GoodData stated.

At the heart of this new layer is the Analytics Catalog, a unified workspace where teams can explore and control their analytical definitions.

Governed and trustworthy AI analytics

The Intelligence Layer weaves governance and business context directly into analytics, bridging the gap between complex data architectures and the day-to-day decisions business users need to make, according to a press release.

Untethered AI agents often hit unpredictable obstacles around data permissions and model context, limiting their impact. By grounding AI in an organization’s own rules, logic, and definitions, GoodData turns traditional reporting into a system where insights seamlessly drive action and reinforce essential business processes.

“Most companies don’t need more dashboards, they need clarity,” commented Roman Stanek, CEO of GoodData. “They need to know their data is right, easy to understand, and ready to use. That’s exactly what the Intelligence Layer is built for.”

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Turning analytics into action

Instead of juggling scattered metrics or debating which numbers are correct, users can rely on a governed environment supported by AI copilots that help generate and validate analytics objects, dashboards, visualizations, metrics, attributes, facts, and datasets with precision, GoodData said. The result is a consistent foundation that ensures everyone is speaking the same analytical language.

Complementing the Analytics Catalog is the Semantic Quality Agent, which acts as a watchdog for the semantic layer. This automated system scans for inconsistencies, missing context, and ambiguous definitions that can quietly distort AI-generated answers. By continually safeguarding metadata quality, the agent helps organizations maintain the integrity of their analytics and prevents issues before they surface in dashboards, tools, or AI outputs.

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AI trust and accountability

Rounding out the Intelligence Layer is AI Memory, a capability that allows organizations to teach their AI assistant to understand and use their specific terminology, acronyms, and operational nuances. AI Memory also allows teams to customize the assistant’s tone, name, and role, integrating AI seamlessly into their product experience.

Rather than offering generic answers, the assistant is equipped to respond in the exact context of the business, ensuring that insights are aligned with how the company truly operates.

“AI shouldn’t feel like a black box. It should feel like a part of your team, one that understands your terminology, your priorities, and your guardrails,” Stanek added. “Together, these elements form a governed, context-aware intelligence system that elevates analytics from passive reporting to an active driver of decision-making. With the Intelligence Layer, people can finally trust the answers they’re getting, they can make decisions faster and with a lot more confidence.”

Pioneering the Next Era of Intelligence

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