As an award-winning company working at the intersection of AI, machine learning, and high-stakes scientific data, Sophelio builds signal-first, provenance-driven systems for environments where reproducibility, interpretability, and operational trust are non-negotiable.
Over the past several years, Sophelio has developed multiple production-grade platforms—including the Archaieus Engine, the Systems Integration and Regression (SIR) Suite, and, its flagship dFL (Data Fusion Labeler) – and has delivered large-scale data and machine-learning systems in collaboration with U.S. Department of Energy–supported programs, national laboratories, federal agencies, universities, and industry partners.
These collaborations include work with organizations such as General Atomics, Sandia National Laboratories, Oak Ridge National Laboratory, MIT, Princeton University, The University of Texas, UC San Diego, Harvard University, HPE, and General Fusion, supporting real-world fusion energy and scientific research initiatives.
Today, Sophelio completes its transition from Sapientai to Sophelio, marking a new chapter for the company following its founding in 2019. This transition reflects an evolution from early research-focused origins to a broader mission: building scalable, production-ready data systems for complex physical, scientific, and industrial domains.
Since its founding, Sophelio has focused on laying strong technical foundations, building long-term partnerships, and developing the core platforms that define the company today. Over the past year, the company has deliberately evolved its identity to reflect both the maturity of its technology and the expanding scope of its work across science, industry, and applied AI.
“This change represents evolution, not departure,” said Matthew Waller, Fusion Energy Machine Learning Tech Lead at Sophelio. “Sapientai is where we built our foundation. Sophelio is who we are now—and where we’re going next.”
Why Sophelio, and Why Now
The Sophelio name signals a company that has moved beyond its early phase and is ready to scale. It reflects a clearer focus on signal-first, provenance-driven data systems and a growing ambition across science, industry, applied AI, and data-intensive decision-making domains.
As the company enters 2026, this new identity aligns with a period of accelerated growth, including:
- New tools extending its signal-first, reproducible data platform
- New projects spanning science, advanced manufacturing, energy, high-tech systems, social sciences, and broad data analytics
- New partnerships and customer engagements across research, industry, and government-adjacent sectors
- A refreshed visual identity, with new colors and design language emphasizing clarity, precision, and momentum
While the company’s name and visual identity have evolved, its mission remains unchanged: to enable rigorous, reproducible, and trustworthy data workflows for complex, multimodal systems—especially where decisions have real-world societal impact.
Looking Forward
The name Sophelio reflects illumination and structure—bringing clarity to complexity and insight to data. It represents the maturity of the company’s platform, the growth of its team, and the scale of what lies ahead.
“This is not just a rebrand,” said Craig Michoski, CEO of Sophelio. “It’s a declaration of readiness. 2026 will be a defining year for Sophelio.”
About Sophelio
Sophelio is an applied AI and machine-learning company focused on transforming complex, high-stakes sensor data into trustworthy, ML-ready datasets. Originating in fusion energy research, the company brings deep expertise in signal-first analytics, data harmonization, and reproducible workflows to industries including advanced manufacturing, robotics, energy, and scientific research.
Sophelio’s flagship platform, Data Fusion Labeler (dFL), enables teams to reliably harmonize, label, and export multimodal time-series data with full provenance—bridging the gap between raw data, analytics, and deployable machine-learning systems in real-world environments.