Riffyn, a global provider of Software-as-a-Service (SaaS) for scientific process design and data analytics, announces the close of a $15 million Series B financing led by M Ventures with participation from Waters Corporation, O’Reilly AlphaTech Ventures, and Plug and Play Ventures. Funds will be used to globally expand sales and scientific services, and to accelerate development of Riffyn’s process development and advanced data analytics technology.
Riffyn automatically integrates heterogeneous scientific data in real time to feed machine-learning and AI. Its uniquely adaptive technology allows scientists to continuously improve R&D processes while seamlessly integrating associated experimental data. Riffyn is used by eight of the top 15 largest biotechnology and pharmaceutical companies to deliver repeatable scientific outcomes, faster product development, and right-first-time technology scale-up.
“I am absolutely delighted to welcome M Ventures and Waters as investors and directors of Riffyn,” said Tim Gardner, Founder and CEO of Riffyn. “They bring a depth of experience and knowledge about the life sciences market that will turbo-charge our already-rapid growth.”
Riffyn has delivered exceptional benefits to its customers’ R&D programs including:
30% reduction in effort (thousands of person-hours saved) to execute scientific workflows
real-time access to multi-experiment data sets for data-driven decision-making
global integration of data for collaboration and machine learning
“We are really pleased to lead this significant investment round alongside such high-quality co-investors and founders. Riffyn brings considerable efficiencies and value to its growing base of R&D customers worldwide,” said Joey Mason, head of M Ventures’ Life Sciences Fund. “The company is becoming a stand-out leader in scientific data analytics and is a compelling example of how digital transformation is creating the lab of the future.”
Maura Fitzpatrick, Senior Director Global Products Marketing noted, “Riffyn’s innovative analytical engine makes study design and data sharing more intuitive. It also helps meet a growing need in our customer base for highly adaptive data analytics and visualization.”
Application of machine learning and AI to scientific R&D data has been hampered by the heterogeneity of data and the constant change of R&D processes. Researchers commonly report spending 80% of their data analysis time cleaning and preparing data. Traditional data systems have failed to address these issues because they lack the structure, flexibility, or data accessibility needed for fast-paced R&D cycles and modern data analytics. Riffyn resolves these issues with “scientific blueprints,” a patented computer-aided-design approach to science that breaks down silos to deliver clean, contextualized, and connected data.