Many enterprises have adopted horizontal, foundation-model AI platforms. But access to the same underlying models does not, by itself, create differentiated intelligence. For highly technical and mission-critical research, general-purpose models may produce broad but weakly grounded answers when they lack access to authoritative technical data, specialized context, and verifiable sources.

The next competitive advantage will come from the intelligence layer surrounding the foundation model: the domain-specific data, ontologies, retrieval capabilities, agent workflows, and source grounding that together form an AI harness. These verticalized systems can transform general-purpose AI into a more specialized capability for research, innovation, and technical decision-making.

Join Steve Hafif, Co-Founder and CEO of Cypris.ai, and Marlene Valderrama, Principal IP Manager and Senior Technology Scout at Halliburton, for a conversation on the state of enterprise AI and how organizations can enhance horizontal AI platforms with verticalized intelligence designed for R&D and innovation.

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Most IP organizations are making high-stakes capital allocation decisions with incomplete visibility – relying primarily on patent data as a proxy for innovation. That approach is not optimal. Patents alone cannot reveal technology trajectories, capital flows, or commercial viability.

A more effective model requires integrating patents with scientific literature, grant funding, market activity, and competitive intelligence. This means that for a complete picture, IP and R&D teams need infrastructure that connects fragmented data into a unified, decision-ready intelligence layer.

AI is accelerating that shift. The value is no longer simply in retrieving documents faster; it’s in extracting signal from noise. Modern AI systems can contextualize disparate datasets, identify patterns, and generate strategic narratives – transforming raw information into actionable insight.

Join us on Thursday, April 23, at 12 PM ET for a discussion on how unified AI platforms are redefining decision-making across IP and R&D teams. Moderated by Gene Quinn, panelists Marlene Valderrama and Amir Achourie will examine how integrating technical, scientific, and market data collapses traditional silos – enabling more aligned strategy, sharper investment decisions, and measurable business impact.

Register here: https://ipwatchdog.com/cypris-april-23-2026/

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In this session, we break down how AI is reshaping the R&D lifecycle, from faster discovery to more informed decision-making. See how an intelligence layer approach enables teams to move beyond fragmented tools toward a unified, scalable system for innovation.

In this session, we explore how modern AI systems are reshaping knowledge management in R&D. From structuring internal data to unlocking external intelligence, see how leading teams are building scalable foundations that improve collaboration, efficiency, and long-term innovation outcomes.