When Jeremy Antoniuk moved from Virginia to Austin early in his career, he was already drawn to the challenge of building companies. With a background in the U.S. Air Force as an air traffic control radar technician, Antoniuk had developed a keen ability to dissect complex systems, understand them from multiple levels, and create order from chaos. That mindset would become the foundation for a career spent scaling some of the market research industry’s most recognized technology companies.
Antoniuk went on to help grow e-Rewards from 20 employees to over 1,300 during his decade with the company, ultimately leading global operations. Later, he played a similar role with a smaller startup, scaling it from a handful of employees to 75 people and an eight-figure revenue. Both experiences cemented his expertise in transforming scrappy startups into operationally mature organizations — and both were squarely in the market research industry.
But they also revealed a recurring frustration. Despite decades of investment in research technology, the industry had grown more fragmented, not less. Researchers were spending more time stitching together tools and cleaning data than generating insights. Worse, the arrival of AI had created more confusion than clarity — most platforms were bolting AI onto legacy infrastructure that was never designed for it.
The Birth of Scalafai
That frustration became the seed for Antoniuk’s latest venture, Scalafai, which launched with a clear and urgent mission: build the AI-native market research platform the industry has been waiting for, designed from the ground up by researchers who have spent their careers living inside the problem.
As Antoniuk puts it, Scalafai “gives researchers their time back.” Rather than forcing teams to navigate a patchwork of fragmented tools, Scalafai’s platform — Scalafai Studio — supports the full research lifecycle through AI agents that handle survey design, programming, quality checks, fielding, and insight delivery. What once took days and cost thousands of dollars can now be completed in hours for a fraction of the price.
“The research industry doesn’t need another point solution,” Antoniuk explained. “It needs a platform that understands research deeply enough to actually replace the workflow, not just automate one step of it.”
Built for the Real Problem
The innovation lies in Scalafai’s combination of vertical AI expertise and real-time quality enforcement. Survey fraud has plagued the market research industry for over two decades, and the problem has only worsened as bad actors have grown more sophisticated. Scalafai addresses this head-on with automated fraud prevention and data quality checks built directly into the fielding process — not bolted on after the fact.
At a recent CEO Summit for the Insights Association attended by 130 industry leaders, AI adoption was identified as the number one challenge, with no viable solution. Scalafai is building directly into that gap, and early customer feedback has been unambiguous, with customer statements like, “total game changer.” And similar comments like, “if I had Studio, I would not have had to re-field the entire study we just completed.”
Antoniuk likens the platform to bringing on a seasoned researcher who never sleeps. “If someone shows up without context, they’ll struggle to help. But if they understand the methodology, the objectives, and the standards the industry demands, they can do extraordinary work. Scalafai gives AI that research context so it can actually drive outcomes,” he concluded.
Rethinking the Research Stack
Scalafai is entering a market where frustration with existing tools runs deep. Legacy platforms, averaging 20 years old, are struggling to retrofit AI onto infrastructure never designed for it. Newer entrants have modern tech but lack the research rigor required for complex, enterprise-grade projects. Scalafai occupies the position neither can claim — deep research expertise built into a modern, AI-native platform.
The business model reflects this positioning. Clients purchase utilization credits with unlimited seats, lowering the barrier to entry while allowing accounts to grow naturally as research volume increases. An integrated sample distribution layer means clients can design, field, and analyze research entirely within the platform — no third-party suppliers, no context switching.
The economics are striking. An average research project that previously cost $4,000 or more and took days to complete can now be executed for $400 in hours.
Building in Austin’s AI Community
Getting Scalafai off the ground required the same instinct Antoniuk applied throughout his career: get in the room, even when it’s uncomfortable. He credits Austin’s AI community with accelerating the company’s early development.
“I’ve always been an introvert,” Antoniuk admitted, “but I pushed myself to go to events. That’s where I met the person who would become our CTO, and from there we built a phenomenal team.” That decision embedded Scalafai in Austin’s fast-growing AI ecosystem and has been validated by recognition across multiple pitch competitions and a 2025 nomination for the Opportunity Austin A-List Awards in the AI Standout Innovation category.
Looking Ahead
With pilots underway and a full product launch planned for April 2026, Scalafai is focused on converting early momentum into a repeatable growth engine. The company is targeting Series A readiness by Q1 2027, with a financial model that projects nine-figures in annual revenue by 2029 — profitable by year two, with a burn multiple that signals exceptional capital efficiency.
For a $140 billion industry still running on outdated processes, Scalafai represents something the market has been asking for and failing to find: a platform built by insiders, designed for the way research actually works, and powered by AI that finally understands the difference.