The Zurich-based startup, once raising €3M to unify fragmented trial data, has now secured a larger funding to develop AI agents focused on managing the complex operational layer of clinical trials.
Clinical trials are among the most data-intensive processes in modern medicine but are inefficiently managed. A single Phase III trial can generate data across numerous sites, hundreds of variables, and diverse regulatory frameworks.
The software tools used to manage this complexity were primarily designed for storage rather than intelligence.
Rivia, a Zurich-based company, has been creating a unified data platform for biotech clinical trials since 2022. It announced raising €13 million in a new funding round to enhance its agentic data engine, a system where AI agents actively provide insights, highlight anomalies, and assist in coordinating trial operations beyond just storing and visualizing data.
The company raised €3 million in seed funding in June 2024, led by Speedinvest, to establish the foundational data infrastructure. The new funding marks a significant increase in ambition and capital, reflecting Rivia’s progress with early biotech clients and the broader trend in enterprise AI towards active systems.
The core challenge Rivia is tackling is fragmentation. Clinical trial data comes from various sources including electronic data capture systems, patient wearables, laboratory instruments, site management software, and regulatory filings, often through different vendors, in different formats, and with different update cycles.
Research teams spend much time reconciling these data sources instead of extracting insights from them.
Rivia’s platform integrates these data streams into a single environment. Its AI layer, now named an agentic data engine, uses large language model-based agents to answer questions about trial status, identify enrolment risks early, and flag data quality issues in near-real-time.
The company claims to have deployed the platform with biotech clients conducting active trials but has not disclosed client numbers or trial scales.
Clinical trials are conducted in a highly regulated environment. The US FDA and the European Medicines Agency enforce stringent requirements on data integrity, audit trails, and validation documentation.
An AI system in this environment must not only perform well but be explainable and auditable, unlike general-purpose AI tools.
This regulatory complexity is both Rivia’s challenge and its advantage. A company capable of building AI agents within the FDA and EMA compliance frameworks, instead of around them, has a defensible position that general-purpose AI tools cannot easily replicate.
It remains unclear if Rivia has achieved regulatory readiness or is still working towards it, based on public information.
The market for AI in clinical trials has seen substantial investment in 2025 and 2026, with competitors like Medable, Veeva, and other smaller startups focusing on different aspects of the trial process.
Rivia’s hypothesis is that the data layer, which connects all components, is the most valuable part of the architecture. With €13 million in funding, it has the resources to test this theory.