A trio of former Palantir executives who helped spearhead that company’s Life Sciences practice have founded a startup called Perceptic that is building an end-to-end AI platform for drug development, handling everything from drug discovery to clinical trial design. The company emerged from stealth today and announced a $12 million seed funding round.
London-based venture capital firm Accel led the funding round, alongside Air Street Capital and Elder Gull. The company’s valuation following the funding round was not disclosed.
Perceptic said its software is already being used by multiple top-tier pharmaceutical companies, though it was only allowed to name CSL, the Australian biotechnology company.
In the past two years, numerous startups have sprung up to use AI to speed drug discovery. This includes Isomorphic, a spin out from Google DeepMind, robotic lab pioneer Recursion, Insilico Medicine, and many others. But so far, no AI-discovered drugs have made it all the way through human clinical trials and been approved for sale, leading some to question whether AI is living up to the hype around revolutionizing drug development.
Tilman Flock, Perceptic’s cofounder and CEO, is a bioscience researcher who spent nearly seven years at Palantir, building the company’s commercial AI platform and helping life sciences companies use it. He tells Fortune that most AI startups targeting drug development have focused on improving just one particular part of the complex process, such as predicting protein structures, or looking for a molecule that will bind with a particular site on a target protein, or trying to optimize the recruitment of patients for clinical trials. Perceptic, by contrast, is pitching itself as the “connective tissue” between those discrete AI tools and the proprietary internal and external data that pharmaceutical companies use to make decisions.
“For years, the industry has tried to improve each part of the [drug discovery] process separately, but that’s a linear process where insight dies at every handoff,” Flock said.
Perceptic’s platform is “infrastructure and model agnostic,” Flock said, meaning customers can plug in their own data, hardware and AI models, while Perceptic acts as the layer that ties them together.
Perceptic is targeting three areas of pharma R&D. The first is scouting external assets that biotechnology companies have developed and that big pharma companies look to license. The startup says its system can compress the scientific due diligence needed to assess these drug candidates from weeks to hours.
The second area where Perceptic is focusing is helping pharma companies choose which indications to pursue in clinical trials, a decision that Flock said can swing the fate of investments worth millions of dollars.
The third is building a “data foundation” for clinical trial design which the company says has produced a 50-fold increase in clinical data extractions.
Sonali De Rycker, the Accel partner who led the firm’s investment, said she was won over by the idea that Perceptic’s software can “follow the drug” through the entire life cycle of development rather than being pitched towards a particular departmental silo within a big pharma company. “From the point at which you have hypothesis and evidence all the way to when you’re designing the clinical trial, and everything you do in between … it makes no sense for it to be siloed,” she told Fortune.
De Rycker said Accel had been tracking Flock and his co-founders, Martin Copes and Zaki Trache, while they were still at Palantir, where the trio were key engineers on AIP, and met them shortly after they decided to leave. The firm invested roughly a year after that first meeting, by which point Perceptic had moved beyond pilots into paid production deployments, she said. The team has grown to about 20 employees today, Flock said.
Pharmaceutical companies, Flock said, tend to draw on three buckets of data: public knowledge, such as patents and literature; internal proprietary data accumulated over years of research and clinical trials; and external datasets purchased from consultants and data vendors. Perceptic can harmonize all three types of data, he said. The system uses “AI workers,” or AI agents, that are tuned to different data types to hunt for insights or optimizations.
Pharmaceutical customers need to know the provenance of any data used to make a decision, Flock said. As a result, they cannot tolerate AI hallucinations, where an AI model invents or conflates information. Perceptic’s AI system allows customers to trace every claim back to its source, he said.
De Rycker argued that Perceptic’s approach reflects a broader pattern in enterprise AI, in which platforms increasingly unify workflows and data across multiple departments rather than offering standalone tools. She added that these platforms can be “almost a new source of truth,” potentially replacing—or at least relegating to the background—traditional databases and enterprise resource planning software.
She added that Perceptic has a “right to win” from Europe given the concentration of pharmaceutical talent in Switzerland and the U.K. Most of the company’s engineering is in London, drawing in part on Palantir alumni, Flock said; many of its customers are in the United States, where Perceptic plans to expand its presence.
Nathan Benaich, the founder and general partner of Air Street Capital, said in a statement that pharma’s next R&D leap “won’t come from a thousand better point tools, or from frontier models alone” but from an operating system “that connects data, decisions, and context across a 15-year process.”
Flock said the bulk of the seed money will go into engineering and growing Perceptic’s customer base. “We’re far beyond product-market fit,” he said. “It’s about scaling out.”
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