Stardog Names Navin Sharma Chief Product Officer to Lead Next Phase of Semantic AI Innovation

Promotion reflects company momentum as enterprises build agentic AI systems that require trusted, contextual data

NEW YORK, May 11, 2026 /PRNewswire/ -- Stardog today announced the promotion of Navin Sharma to Chief Product Officer, reinforcing the company's leadership in powering the next generation of enterprise AI through its Stardog semantic AI platform.

As enterprises move rapidly toward agentic AI, where intelligent systems autonomously analyze data, orchestrate workflows, and support decision-making, the lack of trusted, contextual enterprise data remains a critical barrier to scale. Stardog addresses this gap by providing a semantic layer that connects enterprise data where it lives, models its meaning, and enables AI systems to reason across it with transparency, governance, and trust.

Defining a New Category: Semantic AI Infrastructure for the Agentic Enterprise

Stardog is defining a new category of enterprise software: Semantic AI Infrastructure for the Agentic Enterprise. This emerging layer sits between fragmented enterprise data and AI systems, providing the contextual foundation required for agents to operate reliably in complex, mission-critical environments. By unifying knowledge graphs, data integration, and generative AI capabilities, Stardog enables organizations to move beyond disconnected AI pilots toward scalable, production-grade agentic systems.

Sharma will lead global product strategy and execution as enterprises accelerate investment in this new foundation for AI.

"Navin has been instrumental in shaping our product vision and building the platform our customers rely on," said Craig Harper, CEO of Stardog. "As enterprises adopt agentic AI at scale, the ability to ground systems in trusted, contextual data becomes essential. Navin's leadership will help Stardog continue to define this next era of enterprise AI infrastructure."

Under Sharma's leadership, Stardog has expanded its capabilities across knowledge graphs, data integration, and generative AI, delivering a unified Semantic AI platform that enables organizations to connect siloed data while maintaining governance, explainability, and control.

"Navin brings a rare combination of technical depth and disciplined product execution," said Evren Sirin, CTO and Co-Founder of Stardog. "He has helped evolve Stardog into a platform purpose-built for AI agents that must reason across complex enterprise data with accuracy and trust."

A seasoned enterprise software executive, Sharma has a strong track record of building and scaling B2B data and AI products, translating emerging technologies into commercially successful offerings aligned with customer and market needs. He is widely recognized for combining technical depth with user-centered product leadership and for guiding teams through periods of growth and transformation.

"We are building the cognitive backbone for the future of work powered by autonomous agents", said Sharma. "Stardog provides the semantic control plane where humans and agents collaborate as knowledge engineers to capture, share and scale meaning across complex enterprise domains like manufacturing supply chain and life sciences R&D and deliver outcomes that are explainable, trusted, and actionable."

About Stardog

Stardog is a Data and AI company providing the semantic foundation for the agentic enterprise. Its mission is to strengthen artificial intelligence with human intelligence and empower organizations to make critical, data-driven decisions across every level of the enterprise.

The Stardog Semantic AI Platform connects enterprise data where it lives and adds the semantic context AI needs to understand it, enabling organizations to build trusted AI applications and deploy intelligent agents that can reason, explain, and act. Built on World Wide Web Consortium open standards, Stardog is trusted by organizations including NASA, Boehringer Ingelheim, and Raytheon.

Learn more at www.stardog.com

Media Contact:
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SOURCE Stardog