Rivia Raises $15M to Modernise Clinical Trial Data with AI

Rivia, a data infrastructure company based in Zurich, has announced a $15 million Series A round led by Earlybird, with participation from Defiant, Speedinvest, Amino Collective, and Nina Capital. The company focuses on addressing longstanding inefficiencies in clinical trial data management.

Over the past three years, Rivia has built what it describes as the first reusable intelligence layer for clinical trials. This system integrates thousands of heterogeneous data files in real time, applying scientific logic tailored to each study, and feeds harmonised data into operational workflows. The approach is designed to enable more proactive and efficient decision-making.

On this platform, Rivia is launching a suite of embedded artificial intelligence (AI) agents. The first agent, Spark, converts natural language queries into publication-grade clinical visualisations. Future agents will handle tasks such as data quality monitoring and oversight, supporting earlier detection of data deviations, intelligent prioritisation, and improved accountability.

The funding and product launches occur amid tightening regulatory requirements. New guidance from the U.S. Food and Drug Administration (FDA) encourages innovation in clinical trial methods and mandates more proactive risk and compliance management. This shift increases demand for robust, adaptable data systems in an industry where clinical trial returns have declined significantly over the last decade.

Clinical trial data infrastructure often remains fragmented, relying on spreadsheets and disconnected vendor systems. According to Rivia CEO and Co-Founder Erik Scalfaro, teams frequently download and manually merge files, or hire programmers to create bespoke analytics pipelines for each study — an approach that is costly, slow, and difficult to scale. Existing systems in the sector, such as those offered by Veeva and Medidata, were originally designed for compliance, not real-time integration across multiple sources.

Today’s clinical trials generate vast and diverse data streams from labs, genomics, wearable devices, and more. Single-vendor offerings increasingly cannot keep pace. Scalfaro argues that what is lacking is a technology layer that models trial logic so data from disparate sources can be rapidly and consistently interpreted.

Rivia’s deliberate strategy was to first build a unified and reusable data engine before deploying AI capabilities. Scalfaro emphasises that AI alone cannot address data quality or operational complexity without a reliable data foundation. With this infrastructure, AI systems can deliver more accurate insights and support vertical, trial-specific workflows.

Biotech companies using Rivia have reportedly avoided costly trial disruptions and accelerated decision-making, according to Scalfaro. As the company’s ontology library grows with each new trial, its AI-enabled system becomes increasingly robust. The company’s ultimate aim is to reduce clinical trial costs by up to 50% by automating manual processes with scalable AI agent systems.

Scalfaro also highlights the long-term potential of AI for transforming clinical trial design. Adaptive and decentralised approaches could be enabled by AI’s capacity to manage complexity and detect actionable patterns in large datasets. However, strong scientific oversight will remain crucial as regulatory authorities scrutinise these new methodologies.

Earlybird Partner Christian Nagel commented that Rivia’s unified intelligence layer could fundamentally improve the speed, cost, and quality of clinical operations. Andrea Zitna of Speedinvest also noted Rivia’s focus on foundational data infrastructure as its core innovation, with agentic intelligence now being layered atop that base.

Rivia plans to expand its team in Zurich and Boston as demand grows. By targeting the underlying causes of cost and delay in clinical development, the company aims to accelerate the delivery of new therapies and strengthen the foundations of medical innovation.

tech.eu