Native AI, a market intelligence platform startup, today said that it has raised $3.5 million in seed funding.

The company aims to enable brands to build digital clones of their customers using the power of generative artificial intelligence to answer questions and provide insights. The funding round was led by Jumpstart Ventures and Ivy Ventures, with participation from 11 Tribes Ventures and Connetic Ventures.

The company’s platform is powered by its own proprietary generative AI model that uses real-time industry, consumer and product data to create what Chief Executive Frank Pica calls customer “digital twins” of target customers and consumer bases. The users of the platform can interact with these digital twins and ask them questions about products, preferences and interests and get responses and insights into their behaviors.

Speaking to SiliconANGLE, Pica said that the team first harnessed natural language processing, a type of AI capable of analyzing human speech, to take raw, unstructured customer feedback and create a better connection between brands and their consumers.

“Starting with natural language processing, we very quickly realized that we could generate responses, summaries and quick insights using that raw data,” Pica said. “Then about a year and a half on, the vision became, ‘Could we actually clone individuals using AI and treat those just as you would a focus group or a survey?’”

Using the interface, users can ask questions such as “What flavors are you most likely to buy?” or “What color of lipstick are you most likely to purchase?” The AI will answer with generated text based on how the customized digital twin audience would reply.

What separates Native from other generative AI models on the market, such as OpenAI LP’s GPT-4, is that Native’s internal AI is not open to nonspecific public datasets and is trained on carefully curated first-party and third-party data chosen for the task. Native also allows its premium users to see the actual sources that it uses for specific recommendations and answers.

When a user queries Native’s AI, Pica explained, they can configure what particular audience they want to talk to, which personas or customer base or even the company’s specific customer base. They can even set it to build an audience of digital clones based on the competitor’s customers. This allows the AI to provide accurate, targeted and less biased recommendations.

Also, unlike other generative AI models, which operate as a single entity or persona, Native launches multiple AI digital twins at once. As a result, the user receives numerous responses, which can be particularly useful from a marketing perspective.

“We believe this framework is much more conducive to a lot of the work being done today at major consumer goods companies,” Pica said. “For anyone who is doing market research and looking for marketing insights, they typically need multiple responses to help quantify. That’s the biggest key differentiator is the ability to define the audience or digital twin panel up front of who you want to target and get your responses back such as that shopper at Sephora or at Amazon, or thousands of shoppers.”

In addition to its digital twin service, Native’s platform also allows users to monitor product, industry and competitor performance daily through the analysis of consumer reviews from major retailer websites, such as Amazon, Walmart and Target. Using its technology, companies can track and measure sentiment and brand health in order to make meaningful marketing choices.

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