• 11 Tribes Ventures and Connetic Ventures joined the round, which was co-led by JumpStart Ventures and Ivy Ventures.
  • Unlike most generative AI platforms trained on nonspecific public datasets, Native allows users to see the actual source(s) for specific recommendations and answers.

Market intelligence platform company, Native AI, announced recently that it has secured USD 3.5 million in seed funding.

By harnessing the capabilities of generative artificial intelligence to generate insights and deliver answers to queries, the business wants to empower marketers to create digital clones of their customers. Jumpstart Ventures and Ivy Ventures co-led the fundraising round, and 11 Tribes Ventures and Connetic Ventures also contributed.

The company’s platform is backed by a unique generative AI model that the CEO, Frank Pica, calls customers “digital twins” of target customers and consumer bases. This model leverages real-time industry, consumer, and product data. Platform users can easily interact with these digital twins by asking them questions about products, interests, preferences, and receiving insights into their behaviours in return.

Pica explained that the team’s first step was to use natural language processing, a form of AI that can decipher the spoken language, to gather unstructured, unfiltered customer feedback and improve relationships between businesses and their customers.

Pica said, “Starting with natural language processing, we very quickly realized that we could generate responses, summaries, and quick insights using that raw data. 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?’

Users of the interface can enquire about topics like “What clothing styles are you most likely to purchase?” or “Which lipstick brand are you most likely to buy?” The AI would reply with text it had generated based on what the targeted digital twin audience would say in response.

Native’s internal AI differs from other generative AI models on the market, such as OpenAI LP’s GPT-4, in that it is trained on carefully curated first-party and third-party data selected for the task rather than being open to nonspecific public datasets. Additionally, Native lets its paying customers to view the precise sources it refers to when making recommendations and providing solutions.

According to Pica, when a user asks Native’s AI a question, they can specify the personas, customer base, or even the particular clientele of the company they want to address. They can even configure it to create an audience of digital clones based on the clientele of the rival. As a result, AI can make precise, focused, and less biased recommendations.

Additionally, Native simultaneously launches numerous AI digital twins, in contrast to other generative AI models that only function as a single entity or persona. The user consequently receives a large number of responses, which can be very helpful in terms of marketing.

Pica said, “We believe this framework is much more conducive to much of the work being done today at major consumer goods companies. 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 offering a digital twin service, Native’s platform also enables users to track the daily performance of a product, an industry, and competitors by analyzing customer reviews from well-known retailer websites like Amazon, Walmart, and Target. Companies can track and assess brand health and sentiment using its technology to make informed marketing decisions.