AI research lab NeoCognition lands $40M seed to build agents that learn like humans

Investors are aggressively courting AI researchers to build startups that can make AI more reliable and efficient.

Yu Su, an Ohio State professor leading an AI agent lab, initially resisted pressure from venture capitalists to commercialize his work. He took the leap last year, spinning out his research into a startup after seeing that advances in foundational models could make AI agents truly personalized.

$40M Seed Round

NeoCognition, which Su describes as a research lab developing self-learning AI agents, has emerged from stealth with $40 million in seed funding. The round was co-led by Cambium Capital and Walden Catalyst Ventures, with participation from Vista Equity Partners and angel investors including Intel CEO Lip-Bu Tan and Databricks co-founder Ion Stoica.

“Today’s agents are generalists,” Su told TechCrunch. “Every time you ask them to do a task, you take a leap of faith.”

The Reliability Problem

According to Su, current AI agents suffer from a lack of consistency. Systems such as Claude Code, OpenClaw, and Perplexity’s computer tools successfully complete tasks as intended only about 50% of the time, he said.

Because of this unreliability, agents are not yet ready to function as trusted, independent workers. NeoCognition aims to address that gap by building an agent system that can self-learn to become an expert in any domain, similar to how humans learn.

Learning Like Humans

Su argues that while human intelligence is broad, its real power lies in specialization. When people enter a new environment or profession, they rapidly master its rules, relationships, and consequences.

NeoCognition is building agents to mirror this approach.

“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 missing link to making AI systems reliable enough to operate independently. While it is possible to train agents for autonomous tasks today, they typically must be custom-engineered for a specific vertical. NeoCognition, by contrast, is building generalist agents capable of self-learning and specializing in any domain.

Enterprise Focus

NeoCognition plans to sell its agent systems primarily to enterprises, including established SaaS companies. These customers can use the technology to build AI-powered agent workers or enhance existing product offerings.

Su noted that investment from Vista Equity Partners is particularly strategic. As one of the largest private equity firms in the software sector, Vista can provide access to a broad portfolio of companies seeking to modernize their products with AI.

NeoCognition currently has about 15 employees, the majority of whom hold PhDs.