The New York startup building Digital Twins of real consumers - and asking them the questions your survey never had time to.
Traditional market research is a bet on a stale answer. Native AI's proposition is that you can stop waiting on people and start asking their AI proxies instead. This is either a shortcut or a breakthrough, and the interesting part is that it depends entirely on the data underneath.
Here is the problem Native AI is built around, and it is a very ordinary problem, which is usually where the good companies come from. A large brand wants to know something about its customers - will they like this flavor, this price, this ad. So it commissions research. It recruits a panel, writes a survey, waits several weeks, and receives a deck. By the time the deck arrives, the question has often changed, and the answer describes a world that no longer exists. The research was expensive, it was slow, and it was already a little bit wrong.
Native AI's answer is to skip the waiting. The company builds what it calls Digital Twins: AI-powered proxies of real consumers, assembled from the traces those consumers already leave behind - product reviews, interview transcripts, survey responses, social chatter. You do not schedule a focus group. You open a chat window and ask the twin. It answers in the voice of your audience, you ask a follow-up, and you keep going until you understand something. The company says this compresses research that took weeks into minutes, roughly a 90% cut in timeline.
The obvious objection is that this sounds like asking ChatGPT to pretend to be your customer, which is a party trick, not a research method. Native AI is very insistent on this distinction. A generic large language model will confidently role-play anyone; a Native AI Digital Twin is supposed to be grounded in the actual data of actual study participants, so its answers reflect what those people said and did rather than what a model guesses a person like that might say. The difference is the ground truth, and the whole pitch rests on it.
Whether you find that persuasive probably depends on how you feel about simulation generally. But the company has built its product around the seams where the objection lives, which is a good sign that it takes the objection seriously.
“Consumer research is going through a renaissance and generative AI is leading the way. Imagine being able to chat with a custom clone of your target audience anytime, anywhere.”
— Frank Pica, CEO & Co-FounderNote: 275 million synthetic consumers, ~17 people. That ratio is the whole story about where AI is taking research.
The most honest thing about the product is a slider. Instead of hiding the fact that generative AI can drift from the truth, Native AI puts the trade-off on screen and hands you the control.
Slide toward fidelity and the twin sticks close to what real participants actually said - useful when you need defensible answers. Slide toward creativity and it extrapolates, forecasting how people might react to something they have never seen. Most AI vendors would rather you not think about hallucination at all. Native AI made it a feature you operate.
Native AI sells to brands, agencies and market research firms as a subscription platform, with white-label options for partners who want to run it under their own name.
AI proxies of real consumers, built from reviews, interviews, surveys and social data. Chat with them, ask follow-ups in context, and forecast reactions to new messaging or products.
A customizable workspace to slice consumer data, visualize trends across chart and table formats, and export reports for the rest of the team.
Automated, product-level tracking of your brands and rivals across retailers and distribution channels on the open web.
A toggle between grounded fidelity and predictive creativity, giving researchers explicit control over how far the AI is allowed to extrapolate.
The idea traces to 2017, when the two co-founders were consulting for an early-stage agtech startup and kept hitting the same wall: decisions made on research that was already out of date.
Has worked in AI since 2013 and was a founding member of Decide Technologies, which scaled from three employees to over a hundred. His refrain: partners should not have to become experts in research or in AI prompting.
Co-founded Native AI out of the same consulting frustration and leads operations, framing Digital Twins as the primary way clients dig deeper into insights rather than a one-off gimmick.
The team of around 17 works across two homes - 446 Broadway in New York and 1311 Vine Street in Cincinnati - blending large language models, behavioral science and agent-based simulation. Rounding out leadership: a CTO, a Head of AI, and revenue and partnerships leads.
“Our partners should not have to become experts in research or in AI prompting.”
— Frank Pica, CEO, on the design philosophy behind the 2024 Digital Twins overhaulNative AI closed a $3.5M seed round in April 2023, led by JumpStart Ventures and Ivy Ventures with participation from 11 Tribes Ventures and Connetic Ventures, following an earlier seed tranche.
Co-founders Sarah Sanders and Frank Pica hit on the idea while consulting for an early-stage agtech startup.
Native AI founded in New York; platform built on LLMs, behavioral science and agent-based simulation.
Earlier seed tranche of roughly $1.75M.
$3.5M seed round closed to disrupt market research with generative AI and Digital Twins.
Featured for making consumer insights interactive, using retrieval-augmented generation to ground twins in first-party data.
Flagship Digital Twins feature reimagined: near-immediate responses, contextual conversational follow-ups, and new visualization options.
Search results for talks, product demos and founder interviews. Links open searches on the platforms where Native AI's material lives.