Vectorial Raises $3 Million to Simulate Human Behaviour for Product Research

Vectorial, an AI startup developing human behaviour simulation tools for product development, has raised $3 million in a funding round led by SenseAI Ventures. The company aims to help businesses understand how people may respond to software products, digital experiences and marketing campaigns through AI-powered simulations.

The funding round also included participation from Smilegate, Berkeley SkyDeck, Berkeley AI Research Lab, Dent Capital, Motus Ventures and SUM Ventures. Angel investors, including product leaders from Meta, Shopify and Mastercard, also participated.

Founded by Taranveer Singh, Rahul Garg and Jasmine Kaur, Vectorial is building an alternative to research methods that rely heavily on traditional surveys and interviews. Its platform enables companies to simulate audience responses and test product ideas before committing resources to development or marketing.

How Vectorial Uses AI to Simulate Human Behaviour

Understanding customer behaviour is a central challenge for companies developing new products, launching features or planning marketing campaigns. Traditional user research can provide valuable insights, but collecting responses through interviews, surveys and user studies takes time and resources.

Vectorial aims to address this challenge by using artificial intelligence to model potential user responses. Companies can use its simulations to explore how different audiences might react to a product concept, digital interface or campaign before taking it to market.

The platform is designed to help businesses conduct research more frequently and evaluate more ideas within the same development cycle. Rather than relying exclusively on conventional research methods, teams can use simulated audiences to test assumptions and identify areas that may require further investigation.

AI-based simulations can be useful during early product development, when companies need to compare multiple concepts or refine user experiences. However, simulated responses and real-world customer behaviour are not necessarily identical, making validation through actual users important.

Inside Vectorial's SAPIENS Model

At the centre of Vectorial's offering is SAPIENS, a model that uses socio-demographic, psychographic and behavioural data to simulate target audiences.

According to the company, the model can simulate audiences across web applications, mobile products and AI-based applications. This allows businesses to explore potential user responses across different digital environments.

Vectorial says it has modelled more than 2.5 million people globally, including 500,000 in India. The company also reports having conducted over 30,000 simulations.

These figures indicate the scale at which Vectorial says it is developing and testing its approach to human behaviour modelling. The company is targeting businesses that need insights into different customer groups, particularly when product decisions depend on understanding user preferences and reactions.

Vectorial claims that its model is 30% more accurate at predicting human behaviour than general-purpose large language models. It also says its simulations reproduce findings from previous user studies with more than 85% accuracy.

These are company-reported performance claims. The available announcement does not specify the full evaluation methodology, the benchmarks used or whether the results have been independently verified.

Customers Across Healthcare, Gaming and E-Commerce

Vectorial's customer base includes boAt, GoodRx, Suki AI, Everkind and Concrete Software.

The companies operate across sectors including healthcare, gaming and e-commerce, giving Vectorial a range of potential applications for its human behaviour simulation technology.

In e-commerce, simulated audiences could help teams evaluate product positioning, customer preferences and marketing concepts. In gaming, the technology could support research into how different audiences might respond to game experiences or product features. In healthcare, companies may use audience simulations to explore how users could interact with digital products and services.

These examples illustrate possible applications of the platform rather than independently verified outcomes for individual customers.

The common objective is to give product and research teams another way to evaluate ideas before making decisions about development, design or customer acquisition.

Vectorial's Approach to Scaling Product Research

Vectorial says its customers run approximately 600 simulations each month, equivalent to around 40 user studies. The company also reports that customers conduct up to 20 times more research than they did previously.

If sustained in practice, this approach could allow teams to investigate more product concepts and audience segments without increasing their reliance on traditional research alone.

For companies operating in competitive markets, the ability to test more ideas can be valuable. Product teams frequently need to make decisions about features, user experience, pricing and positioning while working within limited time and budgets.

AI simulations may help narrow down the options that deserve further testing. Actual customer interviews, surveys and live experiments can then provide additional evidence before major decisions are made.

The effectiveness of this model will depend on the quality of the underlying data, the accuracy of the simulations and how well the results translate into real-world behaviour.

What the $3 Million Funding Means for Vectorial

The $3 million round gives Vectorial additional backing as it develops its AI-powered research platform. SenseAI Ventures led the investment, with participation from several organisations and angel investors connected to technology, research and product development.

The announcement does not disclose a company valuation or provide a detailed breakdown of how the newly raised capital will be allocated.

Vectorial operates in a growing area of AI development focused on simulating aspects of human behaviour to support business decisions. Its approach aims to make audience research more accessible and allow companies to evaluate more ideas during product development.

The key question will be whether simulated research can consistently deliver useful predictions across different industries and audiences. If Vectorial can demonstrate that its models reliably complement traditional research, it could become a useful tool for teams seeking faster ways to understand potential customer responses.

For now, its reported customer adoption, simulation volume and research accuracy claims provide an early view of the company's progress as it builds its platform.