Rivia Expands Clinical Trial Intelligence Platform with New AI-Powered Data Findings Module

• New module enables continuous, automated review of clinical trial data, helping drug developers identify issues earlier and track them through to resolution
• Rivia raised $15 million Series A led by Earlybird Venture Capital earlier this year

ZURICH--(BUSINESS WIRE)--Rivia, the data engine powering clinical trial intelligence, today launched Data Findings, an AI-powered data review module designed to reduce costly delays in drug development through automated data checks that surface data issues early and track them through to resolution. The new module is an add-on to Rivia Core, the company’s platform that unifies fragmented clinical trial data into a single, structured foundation that brings together data from different trial systems and vendors.

With the average clinical trial collecting data across tens of thousands of patient-level forms running potentially millions of pages, the potential for unintended errors is high. Standard checks in clinical trial systems catch simple entry errors, but complex checks across forms and data types still rely on custom programming and manual review. Data Findings automates those checks.

“The increasing complexity of drug development requires a fundamentally different approach to clinical data infrastructure,” said Erik Scalfaro, CEO and co-founder of Rivia. “Unresolved data issues regularly delay the transition from clinical trial completion to data analysis and regulatory submission up to several months. Through real-time, automated review of clinical trial data, Data Findings helps clinical teams flag issues during the study, rather than leave them for the final clean-up.”

Scancell, a UK based clinical-stage biotech developing immunotherapies for cancer, is a design partner and the first adopter of Data Findings, and expects to cut end-of-study data cleaning from eight weeks to two.

“Adopting Rivia’s AI-driven clinical data analysis tool Data Findings has enabled Scancell to translate its Phase 2 clinical trial data with greater granularity, confidence and efficiency,” said Joe Thornton, VP, Clinical Operations at Scancell. “Furthermore, this has facilitated in-study data cleaning and quality checks such that we expect to reach Last Patient Last Visit (LPLV) with substantially improved data quality and the potential to bring forward end-of-study database lock by six weeks.”

The launch of Data Findings comes as clinical teams face growing data volumes and evolving oversight expectations. A study by the Tufts Center for the Study of Drug Development and industry partners found that Phase 3 trials collect an average of 5.9 million data points per protocol, with volumes growing 11% annually since 2020. Additionally, Tufts estimates approximately $800,000 in unrealized or lost sales per day of drug-development delay, while direct costs average roughly $40,000 per day for Phase 2 and 3 trials.

Clinical teams need to review more data, earlier, without adding more manual work. Data Findings changes both the scale and timing of review. Its agentic rule builder helps teams create complex checks from plain-language instructions, without programming, while agents continuously surface, group and prioritize findings so clinical teams can focus on what needs attention. This is increasingly important as updated international guidance on good clinical practice emphasizes sponsor oversight and the “appropriate management of data integrity, traceability and security.”

Key features and benefits of Data Findings include:

• Complex checks without programming: An agentic rule builder turns plain-language instructions into validated checks across forms, data types and sources
• Earlier identification of issues: Checks run continuously as trial data changes, surfacing findings throughout the study instead of during final clean-up
• Reliable, consistent review: Rules, findings and follow-up actions sit in one governed workflow, with version control, approvals and a full audit trail

In March 2026, Rivia closed an oversubscribed $15 million (€13 million) Series A financing led by Earlybird Venture Capital, with participation from Defiant and existing investors Speedinvest, Amino Collective and Nina Capital. The funding represents a major milestone in the company's efforts to scale its platform and embedded intelligence capabilities to accelerate clinical development and bring new therapies to market faster.

About Rivia

Rivia is the data engine powering clinical trial intelligence. Its platform unifies fragmented clinical trial data into a structured foundation, helping clinical teams review data, identify issues and make decisions faster throughout a trial. Rivia’s founding team combines pharmaceutical, clinical and engineering expertise. Find more at rivia.com and follow us on LinkedIn.