Over 70 percent of enterprise data goes unused because organizations struggle to verify, structure, and trust it at scale. Inderjit Makkar, Founder of Factacy.ai, joins ExitFund to explain why data accuracy and factual validation are now the real bottlenecks in AI adoption. He shares how Factacy.ai is helping enterprises turn chaotic data into trusted intelligence they can rely on for critical decisions.
This episode goes beyond AI buzzwords to explore what it takes to build dependable systems, why trust is harder than innovation, and how founders can create meaningful impact by solving foundational problems.
What you’ll learn
Why unstructured data is the biggest bottleneck in enterprise AI
How Factacy.ai improves data accuracy and decision confidence
The difference between building AI demos and production-ready systems
Why trust and explainability are essential for AI adoption
Common mistakes companies make when scaling AI solutions
Founder lessons from building in deep-tech and enterprise markets
How to think long-term while building AI products responsibly
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