Striveworks, a pioneer in the field of machine learning, has successfully secured a patent for an innovative data lineage process that promises to redefine transparency and auditability within the industry. This groundbreaking development is poised to streamline operations for data science teams, offering significant time and cost savings while providing comprehensive visibility into machine learning operations (MLOps) processes for management, regulators, and auditors.
The patented process introduced by Striveworks automates the tracking of data and activities throughout machine learning workflows. Notably, this eliminates the need for software modifications or additional actions from developers to capture data lineage, even in scenarios involving external services and databases.
Matthew Griffin, the software engineer at Striveworks who received the patent, emphasizes the importance of recording additional services contributing to the workflow. He explains, “Without this process, developers would need to build a custom one and rigorously enforce compliance across their teams. This process ensures that happens as part of the normal workflow, so developers can focus on their real objectives.”
The Striveworks data lineage process marks a significant advancement over the current MLOps standards. Users can now effortlessly observe activities, outputs, and interactions with external services within their machine learning workflows. Armed with this information, users can make informed decisions about repeating workflows, making non-destructive changes, or reverting to previous states when necessary.
Moreover, this process plays a pivotal role in modern MLOps by enabling the remediation of divergent models. This ensures consistent and reliable results, fostering trust in the technology. Striveworks CEO, Jim Rebesco, underlines the company’s mission, stating, “Our mission at Striveworks is to make artificial intelligence and machine learning models safe, trustable, and seamless parts of business-critical operations.”
With the platform’s lineage system, Striveworks aims to instill confidence in customers regarding the full observability of outputs and interactions with production models. This commitment to transparency and remediation aligns with Striveworks’ overarching vision of making MLOps seamlessly integrate into critical business operations.
About Striveworks
Striveworks is a pioneer in responsible MLOps for national security and other highly regulated spaces. Striveworks’ MLOps platform enables organizations to deploy AI/ML models at scale while maintaining full audit and remediation capabilities. Founded in 2018, Striveworks was highlighted as an exemplar in the National Security Commission on Artificial Intelligence 2021 Final Report. In 2023, Striveworks was recognized on the Deloitte Technology Fast 500TM as one of North America’s fastest-growing companies in technology. For more information, visit www.striveworks.com.