CollectivIQ, a Boston-based startup incubated inside hospitality procurement company Buyers Edge Platform, has launched a tool that simultaneously queries multiple large language models and merges their outputs into a single, more accurate response.
The software pulls answers from ChatGPT, Gemini, Claude, Grok, and up to 10 other models at once. It then searches for overlapping and conflicting information across those responses before producing a fused answer designed to reduce the hallucinations and inaccuracies that have frustrated enterprise users of individual AI tools.
A Problem Built Inside a Company
John Davie, the founder and CEO of Buyers Edge Platform, said the idea grew directly from his own frustrations. When AI tools started spreading across his workforce, he initially encouraged adoption. That enthusiasm faded quickly.
“We had a bit of a wake-up call about a year ago when we learned that if our employees are just using any various AI tools, or even their own license, it could be training on our company information,” Davie said. “We could be essentially edging our competitor.”
Davie explored enterprise AI contracts as a solution, but found them expensive, inflexible, and still prone to producing wrong answers. He described a specific frustration: incorrect, hallucinated responses that employees were embedding into client-facing presentations. He also disliked having to ration access. “We hated having to decide which employees deserved AI,” he said.
His response was to challenge his chief technology officer to build something better internally. CollectivIQ was the result.
How the Software Works
CollectivIQ queries models from OpenAI, Anthropic, Google, and xAI simultaneously through their enterprise APIs. The platform processes the diverging and converging outputs from each model to generate a synthesized answer meant to be more reliable than any single model could produce alone.
On the privacy side, the company says all data from user prompts is encrypted and deleted after each session, a claim aimed directly at the data-leakage concerns that originally spooked Davie about consumer AI products.
The pricing model also breaks from the norm. Rather than locking customers into long-term contracts, CollectivIQ charges by usage. The company absorbs the token costs from the underlying model APIs and passes a consumption-based fee to customers.
“I’m hoping that this is a breath of fresh air for companies that see that they are not going to have to be committed,” Davie said. “They’re only going to pay for the value they get out of it.”
From Internal Tool to Public Product
CollectivIQ began rolling out internally at Buyers Edge Platform at the start of 2026. After a strong initial response from employees, and after Davie recognized that Buyers Edge customers were wrestling with the same AI adoption hesitation, the company decided to release the product publicly.
The startup is currently self-funded entirely by Davie, who said he plans to seek outside capital later in 2026.
For Davie, the process has carried a personal dimension. Nearly 28 years after launching Buyers Edge Platform, he finds himself back in the early-stage grind. “It does feel like way back in the day and we are doing it all over again and being scrappy,” he said, adding that he sits directly with software developers during the build process, the same approach that built his first company.
Photo by Jake Nackos on Unsplash
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