Venture capitalists are actively pursuing AI researchers to establish new companies focused on enhancing the reliability and efficiency of artificial intelligence. Yu Su, a professor at Ohio State University who leads an AI agent research lab, noted that he initially resisted investor pressure to commercialize his academic work. He ultimately decided to launch a startup last year, motivated by breakthroughs in foundational models that he believed could enable genuinely personalized AI agents.

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His company, NeoCognition, which he describes as a research lab dedicated to creating self-learning AI agents, has recently come out of stealth mode with $40 million in seed funding. This investment round was co-led by Cambium Capital and Walden Catalyst Ventures, and included participation from Vista Equity Partners as well as angel investors such as Intel CEO Lip-Bu Tan and Databricks co-founder Ion Stoica.

Su points to a fundamental issue of inconsistency in current AI systems. He explained that existing agents, whether from tools like Claude Code, OpenClaw, or Perplexity’s computer tools, successfully complete tasks as intended only about half the time. “Every time you ask them to do a task, you take a leap of faith,” he remarked.

NeoCognition aims to address this by developing an agent system capable of self-learning to become an expert in any domain, mimicking the way humans learn. Su argues that while human intelligence is broad, its true strength lies in our ability to specialize. When entering a new environment or profession, people can quickly master its specific rules, relationships, and consequences. NeoCognition is building agents to replicate this precise process.

“For humans, our continued learning process is essentially the process of building a world model for any profession, any environment,” Su said. “We believe for agents to become experts, they need to learn autonomously to build a model of any given micro world.”

Su sees this capacity for rapid specialization as the crucial missing element needed to make AI work reliably on its own. While it is possible to train agents for autonomous tasks, they typically must be custom-engineered for a specific vertical. NeoCognition distinguishes itself by building generalist agents capable of self-learning and specializing in any domain.

The company plans to sell its agent systems to enterprises, including established SaaS companies, which could use them to create agent-workers or to enhance their existing product offerings. Su emphasized that the investment from Vista Equity Partners is particularly valuable for this reason. As one of the largest private equity firms in the software sector, Vista can provide NeoCognition with direct access to a vast portfolio of companies seeking to modernize their products with AI.

NeoCognition currently employs about 15 people, most of whom hold PhDs.