At some point, the problem flipped from information access to information overload.
Long before ChatGPT became mainstream, Palm Beach-based Nicholas Mohnacky was already thinking about what happens when the volume of information outpaces our ability to make sense of it. Reports, podcasts, research papers, conference talks… useful on their own, but fragmented when you actually need answers.
“We sort of have hit our limit as humans in the information age,” Mohnacky told Refresh Miami. “There’s so much information that you don’t have time to process it all.”
That realization led him to launch bundleIQ in 2018 with a clear idea: surface the right piece of knowledge at the right time.
Early on, the platform focused on personal knowledge management, attracting journalists, analysts, and researchers. Users could gather content from multiple sources and query it in a structured way. But the company’s direction sharpened as AI tools entered the mainstream.
While much of the market leaned into large language models, bundleIQ stayed focused on the underlying data.
“The problem with a lot of these tools is that they’re LLM-first,” he said. “They focus on generating responses, but not on how the data is actually organized, structured, and trusted.”
That gap becomes obvious in real use. AI tools can generate answers, but often struggle to show exactly where those answers come from. For professionals making decisions, that creates friction.
“You can’t just be led blindly by AI,” Mohnacky asserted. “You need to know where the information is coming from.”
BundleIQ built around that need. Its system can point users to precise sources – down to a page, paragraph, or moment in a video – reducing the time spent verifying outputs.
As AI adoption grew, another insight became central to the company’s strategy: much of the world’s most valuable information isn’t on the open internet.
“What if we go after all the data that’s not in Google and not in ChatGPT?” Mohnacky said.
That includes private research, conference content, and industry-specific knowledge locked behind portals. In response, bundleIQ developed new products like Alani Connect, which organize this type of content into structured datasets that users can interact with directly.
Instead of searching broadly, users can query curated sources tied to specific domains – whether that’s venture capital, healthcare, or policy.
“People want AI-powered answers,” he said. “But they also need data they can trust.”
That trust often comes from established institutions. In high-stakes areas, the difference between a credible source and an anonymous one matters.
“I don’t really care what someone on Reddit says about tax credits,” he added. “I need a trusted source.”
The company is now working with organizations to ingest large volumes of proprietary content and make it usable through AI. At a recent project with the Center for BrainHealth in Texas, bundleIQ processed hundreds of files tied to an event, allowing users to ask questions and trace answers across research, talks, and presentations.
At the same time, the platform is expanding beyond content into community. As AI agents take on more tasks, Mohnacky believes the differentiator will shift toward networks. That’s why bundleIQ is building features that allow users to connect around shared knowledge, turning content ecosystems into active communities rather than static libraries.
The company has raised a seed round backed in part by Florida Opportunity Fund through DeepWork Capital and is preparing for a Series A. Today, the team remains tight, with seven employees, but the focus is on scaling access to trusted data.
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