Investors are aggressively courting AI researchers to create startups that can make AI more reliable and efficient.
Yu Suan Ohio State professor who leads an artificial intelligence agent lab, said he initially resisted pressure from VCs to commercialize his work. He finally took the leap last year and turned his work into a startup when he saw that advancing the underlying models could make agents truly personalized.
NeoCognition, a startup Su describes as a research lab developing self-learning AI agents, just came out of stealth with $40 million in funding. The round was led by Cambium Capital and Walden Catalyst Ventures, with participation from Vista Equity Partners and angels including Intel CEO Lip-Bu Tan and Databricks co-founder Ion Stoica.
“Today’s agents are generalists,” Su (pictured right) told TechCrunch. “Every time you ask them to do a task, you’re taking a leap of faith.”
According to Su, the issue is a lack of consistency. Current agents, whether from Claude Code, OpenClaw or Perplexity’s computational tools, successfully complete tasks as intended only about 50 percent of the time, he said.
Since agents are still so unreliable, they are not ready to trust them, independent workers, Su told TechCrunch. NeoCognition aims to change this by developing an agent system that can learn itself to become an expert in any domain, similar to how humans learn.
Su argues that while human intelligence is broad, its real strength is our ability to specialize. When we enter a new environment or occupation, we can quickly master its unique rules, relationships, and consequences.
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NeoCognition builds agents to reflect exactly this approach.
“For humans, our ongoing learning process is essentially the process of building a universal model for any profession, any environment,” Su said. “We believe that for agents to become experts, they must learn autonomously to build a model of any microworld.”
Su sees this ability to rapidly specialize as the critical missing link to making AI work reliably on its own.
While it is possible to train agents for autonomous tasks, they must be tailored for a specific company. NeoCognition is different because it creates agents that are generalists capable of self-learning and specializing in any domain.
NeoCognition intends to sell its agent systems primarily to enterprises, including established SaaS companies, who can use them to build working agents or to enhance existing product offerings.
Su emphasized that an investment from Vista Equity Partners is especially valuable for this reason. As one of the largest private equity firms in the software space, Vista can provide NeoCognition with direct access to a vast portfolio of companies looking to modernize their products with AI.
NeoCognition currently has approximately 15 employees, the majority of whom hold Ph.D.
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