$10 Million Round For Agentic AI Engineer, Led By Former Google CEO’s Venture Firm

Berkeley-based IntuigenceAI is emerging from stealth this week with $10 million in seed funding. IntuigenceAI’s Agent achieved 81% first-time pass rate on the standardized NCEES Professional Engineering test beating ChatGPT by eight times. Passing the PEE exam is something that takes engineers with advanced degrees several years of work experience to achieve. The funding comes as manufacturing faces a massive workforce shortage with nearly half of experienced engineers set to retire within the decade.

Founded by Moe Tanabian, a former Microsoft VP who previously led the company’s Azure IoT and Industrial AI Software business, IntuigenceAI has developed what it calls “synthetic engineers.” The AI agents digitize the technical blueprints and other specialized and specific data that runs factories, plants and refineries. These diagrams along with real time industrial IoT data guide everything from daily operations to half billion dollar maintenance projects.

IntuigenceAI is already in pilot use at several major corporations, including in the energy and industrial manufacturing sectors. In one case, the system was tasked with designing a critical workflow for a downstream refinery. In another, it helped a multinational industrial company audit over 2,000 pages of technical documentation for contractual compliance and risk. Ibrahim A-Syed, head of Digital Transformation at Celanese, a Fortune 500 chemical manufacturer, says that “before IntuigenceAI’s synthetic AI engineers, it was unimaginable that operational workflows can be automated so quickly. The industry is used to months not hours,” said A-Syed.

Tanabian said due to their highly focused training, IntrigenceAI’s synthetic engineers don’t hallucinate or offer “it depends” answers. Instead, they operate within strict confidence bounds and cite every recommendation back to a source. “We don’t do general-purpose reasoning. We don’t try to compete with ChatGPT. This is narrow and vertical AI, designed to solve specific, hard engineering problems. Our advantage comes from training on proprietary customer data that’s locked behind corporate firewalls, something general AI providers can’t access.”

The company’s interface resembles a typical design collaboration suite, with chat, document sharing, and task lists. But behind the scenes, each request is handled by a constellation of domain-specific agents, like a safety analyst, a design reviewer, and a compliance auditor, each tuned on technical documents, standards, and process playbooks.

IntuigenceAI is also building what it calls a “domain kernel,” a structured representation of expert engineering knowledge for each field. This is a curated, contextual model of how knowledge is applied inside real engineering workflows. The kernel, Tanabian says, is what allows the system to simulate not just outputs, but judgment.

“In the early days of aviation, pilots had to manually check every surface and instrument. Today, a lot of that has been automated, but we trust the system because we know how it thinks,” said Tanabian. “Our AI will handle the everyday tasks, and pull in humans when necessary to manage the exceptions.”

Process manufacturing represents a $4 trillion market that remains largely under-digitized despite operating some of the world’s most complex industrial facilities, Tanabian explained. “Process manufacturing sounds niche, but it’s actually massive.”

“We’re proud to lead the investment in IntuigenceAI as they build the AI copilot for complex industrial engineering,” said Scott Brady, Managing Partner at former Google CEO Eric Schmidt’s venture capital fund, Innovation Endeavors. “This is a purpose-built system already outperforming top chemical engineers on professional benchmarks. In a $4 trillion sector facing massive workforce challenges, with up to 50% of skilled talent set to retire by decade’s end, solutions like this are essential to keeping the industry running.”

Tanabian says the biggest challenge is culture. “Engineers are skeptical by nature. That’s what makes them good at their jobs, but they spend roughly 30% of their time searching through fragmented document systems. When they see how much time this saves, how much risk it reduces, it becomes a no-brainer.” Tanabian says Intuigence is a force multiplier, enabling lean teams to take on more complex projects without burning out or bottlenecking. “The idea is not to eliminate the engineer. It’s to let the engineer focus on engineering.”