The Zurich-based startup, which previously raised €3M to unify fragmented trial data, has secured a larger round to build AI agents that actively manage the complex operational layer of running a clinical trial.
Clinical trials are, by almost any measure, one of the most information-intensive processes in modern medicine, and one of the least efficiently managed. A single Phase III trial can generate data across dozens of sites, hundreds of variables, and multiple regulatory frameworks simultaneously.
The software tools that research teams use to manage this complexity were largely designed in an earlier era, when the primary goal was storage rather than intelligence.
Rivia, a Zurich-based company that has been building a unified data platform for biotech clinical trials since 2022, announced today that it has raised €13 million in a new funding round to expand what it describes as an agentic data engine, a system in which AI agents actively surface insights, flag anomalies, and help coordinate the operational layer of a trial, rather than simply storing and visualising data.
The company raised €3 million in seed funding in June 2024, led by Speedinvest, to build the foundational data infrastructure. The new round represents a significant step up in ambition and capital, reflecting both the progress Rivia says it has made with early biotech clients and the broader shift in enterprise AI towards systems that act, not just analyse.
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The problem with trial data
The core challenge Rivia is addressing is fragmentation. Clinical trial data flows from electronic data capture systems, patient wearables, laboratory instruments, site management software, and regulatory filings, often through different vendors, in different formats, with different update cycles.
Research teams spend a substantial portion of their time simply reconciling these data sources rather than drawing insight from them.
Rivia’s platform, as described in its earlier materials, integrates these data streams into a single environment. Its AI layer, which the company is now calling an agentic data engine, goes a step further, using large language model-based agents to proactively answer questions about trial status, identify enrolment risks before they become delays, and flag data quality issues in near-real-time.
The company says it has deployed the platform with biotech clients running active trials, though it has not disclosed the number of clients or the scale of trials covered.
Agentic AI meets regulated environments
Clinical trials sit in one of the most tightly regulated environments in any industry. The US Food and Drug Administration and the European Medicines Agency impose strict requirements on data integrity, audit trails, and validation documentation.
Any AI system operating in this environment must not only perform well but be explainable and auditable in ways that general-purpose AI tools are not designed to be.
This regulatory complexity is both Rivia’s challenge and its moat. A company that can build AI agents that operate inside the FDA and EMA compliance frameworks, rather than around them, has a defensible position that a general-purpose AI tool cannot easily replicate.
Whether Rivia has already achieved that level of regulatory readiness, or is building towards it, was not clear from public communications.
The broader market for AI in clinical trials has attracted significant capital in 2025 and 2026, with competitors including Medable, Veeva, and a cohort of smaller startups competing on different parts of the trial stack.
Rivia’s bet is that the data layer, the substrate that connects everything else, is the highest-value position in the architecture. With €13 million now in the bank, it has the runway to test that thesis.
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