Paul Nashawaty

Author: Paul Nashawaty

Author

  • Paul Nashawaty

    Paul Nashawaty, Practice Leader and Lead Principal Analyst, specializes in application modernization across build, release and operations. With a wealth of expertise in digital transformation initiatives spanning front-end and back-end systems, he also possesses comprehensive knowledge of the underlying infrastructure ecosystem crucial for supporting modernization endeavors. With over 25 years of experience, Paul has a proven track record in implementing effective go-to-market strategies, including the identification of new market channels, the growth and cultivation of partner ecosystems, and the successful execution of strategic plans resulting in positive business outcomes for his clients.

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AI Output Governance: The Blind Spot in Enterprise AI Strategy
AI, Application Development, DevSecOps, Enterprise IT Strategy, Machine Learning

AI Output Governance: The Blind Spot in Enterprise AI Strategy

Enterprise AI governance frameworks have focused on access control and data inputs, leaving output quality and compliance largely unmanaged. Markup AI is making... Read more.
Europe's Physical AI Advantage: What Industrial Leaders Need to Know
Agentic AI, AI, AI Governance, AI/ML, Application Development

Europe’s Physical AI Advantage & What Industrial Leaders Need to Know

Europe is leveraging decades of heavy-industry data to build physics-aware AI that American hyperscalers cannot easily replicate. Neural Concept's $100M Series C... Read more.
EU AI Act Delay Widens the AI Insurance Coverage Gap
AI Governance, Application Development, Compliance, Enterprise Software

EU AI Act Delay Widens the AI Insurance Coverage Gap

The EU granted a 16-month extension on AI Act high-risk obligations, but insurers are moving the other way, filing generative AI exclusions into D&O and E&O policies.... Read more.
Enterprise AI ROI Gap: Why Productivity Gains Vanish at Scale
AI, Application Development, Enterprise Software, Machine Learning

Enterprise AI ROI Gap: Why Productivity Gains Vanish at Scale

Enterprise AI is making individual contributors faster while leaving organizational returns largely unchanged. The cause is structural: AI was layered onto inherited... Read more.
EU AI Act Deadline: Why AI Governance Is Now a Global Enterprise Issue
AI, AI/ML, AIOps, Application Development, DevSecOps

EU AI Act Deadline: Why AI Governance Is Now a Global Enterprise Issue

The EU AI Act's August 2 transparency deadline is closer than most North American enterprises realize. Cinchy CEO J. Paul Haynes argues the real challenge isn't... Read more.
HarmonEyes: AI Eye-Tracking for Fatigue and Health Detection
AI, AI/ML, Application Development, Life Sciences

AI Eye-Tracking for Fatigue and Health Detection

HarmonEyes has developed an AI eye-tracking platform that detects cognitive fatigue, stress, and early illness using standard cameras, no proprietary hardware required.... Read more.
Why Data Infrastructure, Not Models, Drives Life Sciences AI
AI, AI/ML, AIOps, Application Development, Cloud, Data Management

Why Data Infrastructure, Not Models, Drives Life Sciences AI

DNAnexus CEO Thomas Laur contends that AI drug discovery stalls not because of model limitations, but because scientific data infrastructure isn't production-ready.... Read more.
Endra's AI MEP Platform Targets the Engineering Bottleneck
AI, Application Development, Enterprise Software, Machine Learning

Endra’s AI MEP Platform Targets the Engineering Bottleneck

Endra, backed by a $50M Andreessen Horowitz Series A, is expanding from Stockholm to New York, San Francisco, and London with an AI platform for MEP engineering.... Read more.