Clinical trials generate reams of data. Getting useful answers from that data? That's historically been a different story.
Rivia, a Zurich-based biotech platform, thinks it has cracked part of the problem. The company recently disclosed that its Spark AI system cut the time required for typical Phase 2 clinical data review tasks by 91%, on average, during an internal evaluation spanning May through July 2025. Those findings were presented at the European Society for Medical Oncology's AI conference in Berlin this past October—a respectable enough stage for what amounts to a bold efficiency claim in an industry where sluggish data processing has long frustrated sponsors and slowed drug development. The company has not disclosed details on the evaluation methodology, nor have the findings undergone peer review or independent verification.
Whether that time savings holds up across sponsors, therapeutic areas, and the messy realities of real-world trials remains an open question. But the promise is enticing, particularly for smaller biotech firms burning cash while they wait for trial data to yield actionable insights.
A Conversational Layer Atop the Chaos
Rivia's pitch centers on eliminating what insiders call "the waiting game." Traditional clinical data review can consume weeks: CROs deliver datasets, statisticians wrangle formats, medical monitors request custom queries, analysts circle back with tables days later. Rinse, repeat.
Spark AI takes a different approach. The platform layers natural-language queries and a conversational assistant directly into patient profiles, allowing clinical teams to interrogate safety data, biomarkers, and patient trends on the fly. No waiting for manual extraction cycles. No emailing a data scientist at 11 p.m. to pull a specific subset of adverse events.
Underneath that interface sits Rivia's Core product, which maps messy, fragmented trial data—often scattered across contract research organizations, labs, and vendor systems—into standardized formats like SDTM (the Clinical Data Interchange Standards Consortium's Study Data Tabulation Model, for the uninitiated). The company says it can go live in 20 to 30 days, with hourly pipeline updates thereafter. That's fast, if true. Legacy electronic data capture systems can take months to configure.
Talent and Capital Backing the Build
Rivia didn't emerge from nowhere. The company was founded in 2022 by three co-founders: Erik Scalfaro (CEO), Tiago Kieliger (CTO), and Henk Johan Streefkerk, who serves as Chief Medical Officer. It closed a €3 million seed round in June 2024, led by Speedinvest, with participation from Nina Capital and Amino Collective. That capital, the company indicated at the time, would fuel engineering hires, client services expansion, and further product development.
More recently, Rivia has made moves to deepen its medical and scientific bench. In September 2025, it brought on Dr. Rich Christie as a strategic advisor. Christie spent years as Chief Medical Officer at AiCure and previously held roles at Roche and Johnson & Johnson—credentials that suggest Rivia is serious about credibility within biopharma circles. A month later, the company added Tristan Heintz, PhD, as a scientific expert.
The company lists clients including Alentis Therapeutics, Abcentra, ENYO Pharma, Omeicos Therapeutics, and Scancell. Its headcount sits somewhere between 11 and 50 employees, clustered in Zurich—a modest operation by Big Pharma standards, but typical for a venture-backed clinical tech startup.
The Incumbents Are Circling
Rivia's 91% time-reduction figure comes with caveats. It's based on an internal evaluation, not peer-reviewed research or an independent audit. The company hasn't disclosed sample sizes, task complexity, or how it defined baseline performance. In clinical tech, self-reported benchmarks can be generous.
Still, the timing is noteworthy. Large incumbents are racing to embed AI across trial operations. Medidata, the Dassault Systèmes-owned giant, has reported that over 500 clinical studies have tapped its AI features over the past decade. IQVIA, another behemoth, recently announced an AI-enabled Clinical Trial Financial Suite slated for general availability in the first quarter of 2026. Neither company is sitting still.
For Rivia, the challenge will be proving that its specialized approach—narrower in scope than the sprawling EDC and CTMS platforms that have dominated trial data management for years—can deliver consistent value across diverse sponsors and therapeutic programs. Biotech sponsors, especially those racing to validate clinical hypotheses before cash runs dry, are a natural audience. But scaling beyond early adopters often means navigating the risk-averse procurement processes of larger pharma organizations.
What's at Stake
Clinical trials remain expensive, slow, and prone to operational inefficiencies. According to industry estimates, bringing a new drug to market costs upwards of $2 billion and takes over a decade, with trial execution representing a significant chunk of both time and expense. Any technology that genuinely accelerates data review could shave months off development timelines and millions off budgets.
Whether Rivia can deliver on that promise consistently—and whether its internal benchmarks translate to external validation—will determine if it becomes a category leader or a cautionary tale in the crowded clinical tech landscape. For now, the company is positioning itself as a faster, more focused alternative to the legacy giants. In an industry where speed increasingly equals survival, that's a bet worth watching.
