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§ Private Profile · Dover, USA
Startup developing a GenAI data layer, integrating enterprise data with human expert knowledge to build expert AI agents for complex industries.
Clarifeye is a software developer operating from an undisclosed location that builds a GenAI-ready data layer designed to enhance generalist large language models by integrating enterprise data with human expert knowledge. The company provides collaborative infrastructure that allows software engineers and subject-matter experts to jointly construct, evaluate, and optimize specialized AI agents that replicate complex human reasoning. This technology is engineered for enterprises where core business value relies heavily on specialized knowledge workers. The platform targets highly regulated sectors, providing scalable automation solutions for corporate customers operating across the law, regulatory compliance, life sciences, and manufacturing industries. The enterprise software startup recently raised €4 million in a 2025 pre-seed funding round to accelerate product development and expand its workforce. Clarifeye was founded by chief executive officer Mathieu Grisolia alongside a team of former leaders from Dataiku.
Clarifeye has raised $8.7M across 2 funding rounds.
Clarifeye has raised $8.7M in total across 2 funding rounds.
Clarifeye has raised $8.7M across 2 funding rounds. Most recently, it raised $4.7M Pre-Seed in October 2025.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Oct 1, 2025 | $4.7M Pre Seed | Gustav VON Sydow | Alexandre Berriche, Jean LUC Robert, Olivier Pomel, Drysdale | Announced |
| Mar 1, 2025 | $4M Seed | — | Further Ventures, Kima Ventures, Motier Ventures, Outrun Ventures, Sequoia Capital, Frederic Montagnon, Pierre Lavaux, Rand Hindi | Announced |
Clarifeye has raised $8.7M in total across 2 funding rounds.
Clarifeye's investors include Gustav von Sydow, Alexandre Berriche, Jean-Luc Robert, Olivier Pomel, Drysdale, Further Ventures, Kima Ventures, Motier Ventures, Outrun Ventures, Sequoia Capital, Frederic Montagnon, Pierre Lavaux.
# Clarifeye: Transforming Expert Knowledge into Scalable AI Systems
Clarifeye is a Paris-based AI platform that converts specialized human expertise into scalable, domain-specific AI agents.[2] The company addresses a critical gap in enterprise AI: while generalist large language models are fast but shallow, and vertical AI solutions are specialized but rigid, organizations in complex sectors struggle to capture and operationalize the tacit knowledge held by their best experts.[2]
Clarifeye's core offering is a "Knowledge Warehouse"—a cloud-native data layer that connects raw enterprise data, human expertise, and large language models to enable teams to build, test, and deploy expert-level AI agents.[4] The platform targets high-ROI use cases in industries where expertise is scarce and institutional knowledge creates bottlenecks: law and regulation, life sciences, and manufacturing.[2] Rather than replacing experts, Clarifeye frees them to focus on collaboration and knowledge creation while AI agents handle consistent execution of complex reasoning tasks.[2]
Clarifeye was founded by Mathieu Grisolia (CEO) and a team including co-founders referred to as "Mat, LPK, Max" in company materials.[4] The company emerged from recognizing a fundamental problem in enterprise AI adoption: organizations are forced to choose between fast but shallow generalist AI and specialized but rigid vertical solutions, neither of which captures the full depth of institutional expertise.[2]
The company raised significant early validation in October 2025, securing a €4 million pre-seed round led by EQT Ventures, with participation from prominent angel investors including Olivier Pomel (CEO and founder of Datadog), Jean-Luc Robert (ex-CEO of Kyriba), and Alexandre Berriche (Fleet).[2] This backing reflects confidence in the founding team's vision and the market opportunity in knowledge operationalization.
Clarifeye sits at the intersection of two major AI trends: the maturation of large language models and the growing realization that raw model capability alone cannot solve enterprise problems requiring deep domain reasoning.
The timing is critical. As organizations move beyond proof-of-concept GenAI projects, they confront the "last-mile problem"—how to integrate AI into workflows where accuracy, consistency, and explainability matter.[2] In sectors like pharmaceuticals, legal services, and manufacturing, a single error can be costly. Clarifeye's approach of encoding expert reasoning into auditable, versionable AI agents directly addresses this need.
The company also reflects a broader shift in AI infrastructure: from monolithic models toward modular, domain-specific systems that combine foundation models with structured knowledge and human oversight. This aligns with enterprise demand for AI that is trustworthy, controllable, and aligned with organizational processes rather than black-box systems.
Clarifeye is well-positioned to capture significant value in the enterprise AI infrastructure layer. The €4 million pre-seed round and high-caliber investor backing suggest the market recognizes both the problem and the team's ability to solve it. The company's focus on "collective intelligence"—where humans and AI agents learn from each other—positions it against the false choice between full automation and manual processes.
Looking ahead, Clarifeye's growth will likely depend on execution in regulated, high-stakes industries where the cost of AI errors justifies investment in knowledge infrastructure. Success in law, life sciences, or manufacturing could establish the company as the standard platform for expert knowledge operationalization, similar to how specialized data platforms have become essential infrastructure in their respective domains. The key inflection point will be demonstrating that domain-specific agents built on Clarifeye's platform genuinely approach expert-level performance while remaining auditable and updatable—a claim that will require sustained customer validation.