Partnering with Minerva

Over the past few years, “AI for marketing” has mostly meant asking a model to help with the surface-level parts of the job: write this copy, summarize this dashboard, generate these audience ideas, draft this campaign brief.

But the bigger challenge in modern marketing sits a layer underneath those prompts. Marketing teams today are operating with fragmented customer data, disconnected tools and inconsistent reporting across a growing number of channels. They have more information about their customers than ever before, but much of that information is not structured in a way that AI can reason over or act on.

AI agents are also context-hungry. In marketing, context means understanding who a brand’s customers are, how they behave, what drives conversion, and what action to take next.

That is why we are excited to partner with Minerva to bring customer context to AI native marketing departments. 

Minerva is AI for marketing leaders. At its core, the company is focused on helping brands turn fragmented customer data into a usable understanding of who their consumers are, what drives their behavior and how to reach them more effectively. The old model asked marketers to spend too much time on data pulls, measurement, reporting, audience modeling, and campaign optimization. Minerva shifts that work to AI, so marketers can spend more time on the parts of the job where human judgment matters most, like strategy, brand, creative direction and taste.

Minerva was founded by Jackson Engles, Daniel Saedi, and Matthew Joseph, three friends from Berkeley who began their careers in data-intensive corners of finance at Lazard, Bridgewater, and Citadel, respectively.

The original insight came from Daniel and MJ’s work with alternative data. In quantitative investing, consumer data could be extraordinarily powerful, but only if it was clean, structured, and reliable enough to support real decisions. They saw both the commercial value of consumer signals and the difficulty of turning fragmented, inconsistent datasets into durable insight. 

Minerva's agents run end-to-end marketing workflows within 24 hours. The platform unifies fragmented first-party data and enriches it with Minerva’s proprietary identity graph and more than 1,000 attributes. Marketing teams can easily build audiences, analyze performance, optimize campaigns, and generate reporting without manually managing every step of the process.

The company is also working with OpenAI on two technical workstreams using unreleased frontier models—an Agentic Data Engineer and an Agentic Data Scientist. The Agentic Data Engineer can profile a customer’s first-party data, understand its structure, write transformation SQL, and validate the output. The Agentic Data Scientist lets marketers use natural language to generate predictive models, turning prompts like “find users likely to book a luxury property in the next 30 days” into trained, validated, and deployed models.

We led Minerva’s seed round because we believed Jackson, Daniel, and MJ had a rare combination of insight, technical ambition, and earned customer empathy. Our partnership with Minerva has only deepened that conviction. Because we work closely with a small number of companies, we have been able to spend real time with the team and see the power of that combination up close. They deeply understand that data is only useful when it is structured well enough to support decisions. And they saw early that the next generation of marketing software should be built around agents that can reason, decide and act with the right context. 

Today, Minerva is launching publicly (read more in Axios here), and the company has signed nearly three dozen customers to date, including the NBA, Juicebox, Luxury Presence, Trust & Will, and Wander. We are proud to be early partners with Jackson, Daniel, MJ, and the Minerva team as they continue to build the context layer for consumer marketing.