TopQuadrant Launches Enterprise Context Platform to Build Trusted AI

TopQuadrant, a pioneer in semantics, data management and AI, today announced the launch of TQ Data Foundation, the context layer for trusted, autonomous agents. The new offering extends TopQuadrant’s position as the knowledge graph platform of choice for Fortune 500 enterprises to provide the contextual foundation needed to power AI applications.

The AI Context Gap

Enterprises are investing heavily in AI, yet many remain stuck in pilot mode. The common assumption is that the bottleneck lies in the model or the data platform. In reality, the constraint is more fundamental: AI lacks access to the context that governs how the enterprise actually works.

Traditional data platforms were built for reporting and analytics, helping teams analyze trends and answer known questions. AI changes the mandate. Modern AI systems interpret, synthesize, recommend, and increasingly act. AI must reason across systems, apply business rules, and trigger workflows with speed and autonomy—a capability which requires more than data. It requires shared meaning.

In most organizations, business meaning is fragmented—definitions vary across systems, logic is hard-coded in pipelines, policies live in static documents, and institutional knowledge resides in people. Humans compensate through experience and judgment. AI systems cannot.

When context is implicit or scattered, AI fills in the gaps with confident approximation—a risk no organization can afford.

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Introducing TQ Data Foundation

TQ Data Foundation is the enterprise context platform to build trusted AI, operationalizing context so AI systems can reason, act, and govern with confidence.

“TopQuadrant provides the missing link that scales trustworthy AI,” said Amar Doshi, Chief Product Officer at TopQuadrant. “The TQ Data Foundation answers our enterprise customers’ needs as they progress from building data foundations for people, to securing trusted, context-driven foundations for AI.”

The TQ Data Foundation platform stands on four key pillars using knowledge graph technology to connect and power context for humans and AI:

– Models – Encode how core business concepts interact so AI can answer questions correctly the first time (commonly implemented as ontologies)
– References – Align critical terms across teams so AI produces consistent answers across systems (products, customers, suppliers, policies)
– Metadata – Ingest metadata from sources such as data lakes, data catalogs and content management systems to describe information in a consistent, discoverable way
– Business Logic – Express unique rules, governance and compliance “as code” to activate context into AI and other applications

Managing the Context Lifecycle

TopQuadrant’s TQ Data Foundation manages the full lifecycle of foundational data and context, from build to change management:

– CAPTURE: Capture and unify business context across people, systems, and documents leveraging AI
– ACTIVATE: Deliver shared context wherever AI is built and deployed (tools, agent frameworks, platforms)
– EVOLVE: Continuously govern and improve context so AI stays aligned, accurate, and trusted over time

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The result is one comprehensive platform to build and manage the context layer in order to deliver AI that is accurate, scalable and trustworthy.

“I am excited to deliver the next stage of data and AI maturity for our customers with the new TQ Data Foundation,” said Nimit Mehta, CEO of TopQuadrant. “As we partner with the world’s largest and most complex enterprises to solve the context gap in AI governance, it is very rewarding to witness the business outcomes of safe, accurate and scalable AI.”

Powered by internal agents, embedded directly into AI pipelines, and actively listening to self-enrich, TQ Data Foundation ensures a scalable data foundation built for the promise and ambitions of Enterprise AI.

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