AI agents don't always understand how companies work. This startup raised $5.2 million to solve that.

AI agents are getting better at completing tasks.

But one startup says the digital assistants don’t actually understand how the companies they’re working for operate.

Now, Zeroset has come out of stealth and raised $5.2 million to build models that give AI agents a constantly updated picture of a company’s operations.

Zeroset’s cofounder and CEO, Akshat Kannan, said today’s AI models have little knowledge of the inner workings of an individual business because that information can be scattered across customer relationship management systems, ticketing, and internal docs.

Nor are AI models typically trained on a company’s proprietary data. “Models off the shelf have no understanding of the dynamics of how an enterprise actually works,” Kannan told Business Insider. “They have no understanding of how the work gets done.” Zeroset’s first product, Nebula, connects to software a company already uses, including Microsoft 365, SharePoint, Outlook, Teams, GitHub, and workplace messaging tools.

It then tracks how information and activity across those systems change over time.

The idea is to give AI agents more than a pile of company documents to search through.

Instead, it wants them to understand the sequence of events and decisions that make up a workflow so that it knows how similar cases were handled previously.

It can then do that work autonomously.

Zeroset was founded in January by Kannan, 18, who dropped out of Stanford this year, and William Zhang, 21, who dropped out of the University of Texas last year to work on the startup.

The company is still in a closed research preview and will progressively expand access to customers rather than do a single broad launch.

The company plans to combine a license component with usage-based pricing that scales with the amount of data and agent activity running through Nebula.

Zeroset said its initial focus is on enterprises and AI-native companies that deploy long-running agents in industries like manufacturing, supply-chain operations, and financial research.

It indirectly competes with companies like Mem0 and Zep, which are building memory infrastructure for AI agents.

Its $5.2 million pre-seed round was co-led by Gradient and 2048 Ventures, with participation from Leblon Capital.

Gradient is a venture capital fund founded by Google in 2017 that focuses on seed and early-stage AI and machine learning startups.

Zeroset has five employees and plans to use its fresh funding to hire researchers and systems engineers, fund early enterprise deployments, and pay for model training.

Kannan said that training is one of its highest costs, and in one peak training run, it spent about $100,000 in two weeks.

Check out the 11-slide pitch deck it used to secure the cash injection: