When AI Lies, Ask 10 Models Instead of One

The $10 Million Problem Every CEO Faces

John Davie had a wake-up call that cost him sleep—and potentially millions. His employees at Buyers Edge Platform were unknowingly feeding company secrets to AI models, essentially "training their competitors." Worse yet, the AI-generated content in their PowerPoint presentations contained flat-out lies.

The hospitality procurement CEO wasn't alone. 47% of enterprises hesitate to adopt AI tools due to accuracy and security concerns. When Davie looked for solutions, he found expensive long-term contracts for models that still hallucinated. His response? Build something better.

When One Brain Isn't Enough

Enter CollectivIQ, Davie's Boston-based spinout that treats AI like a jury trial. Instead of trusting one model, it queries up to 10 different LLMs—ChatGPT, Claude, Gemini, Grok, and others—simultaneously. The system then analyzes overlapping and conflicting information to produce what it calls a "fused answer."

Think of it as crowd-sourcing intelligence. If ChatGPT says the sky is blue, Claude agrees, but Gemini insists it's green, the system weighs the consensus. All data gets encrypted and deleted after use, addressing the privacy nightmare that kept Davie awake.

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The early results from 2026 internal testing were promising. Employee complaints about biased and hallucinated answers dropped significantly. When customers expressed similar frustrations, Davie knew he had a market.

The Real AI Revolution Isn't About Models

Here's what's fascinating: CollectivIQ's business model challenges the entire enterprise AI playbook. While competitors lock customers into expensive annual contracts, CollectivIQ charges by usage. "Pay only for the value you get," Davie promises.

This reflects a deeper truth about enterprise AI adoption. Companies don't want the "latest and greatest" model—they want reliability. One hallucinated fact in a board presentation can torpedo a deal worth millions.

For developers and startups, this raises uncomfortable questions about vendor lock-in. Are we building AI strategies around specific models, or should we be model-agnostic from day one?

Davie, now 28 years into his entrepreneurial journey, seems energized by building again. "It feels like way back in the day," he says, sitting "hand and hand with software developers." Sometimes the best solutions come from CEOs who refuse to accept that "good enough" is actually good enough.