Relyance AI Secures $32M to Enhance AI Data Governance and Compliance

Relyance AI raises $32M to make AI data governance more transparent - SiliconANGLE

Relyance AI raises $32M to make AI data governance more transparent Relyance AI Inc., developer of a governance platform that provides visibility and control over enterprise-wide data, today announced a $32.1 million Series B funding round to scale operations and address the rapidly growing demand for more transparency around the training and use of artificial intelligence models. The four-year-old startup, which secured a $30 million funding round in 2021, is addressing the need for organizations to better understand where their data lives and how it is used in a climate of increasing regulation. A recent study by Precisely (formerly Syncsort Inc.) Found that only 12% of 565 data and analytics professionals who were surveyed said their data is of sufficient quality and accessibility for effective use in AI. Two-thirds said they don't completely trust the data they rely on for decisions. More than one-quarter of the Fortune 500 identified AI regulation as a risk in annual reports to the Securities and Exchange Commission. Relyance said the core of the problem is that privacy and security have been seen as separate challenges, with privacy teams being unaware of whether their commitment to regulations and customers is being met, while security teams typically don't know what data should be in AI models. Relyance's technology scans all of an organization's data, including in applications, AI models and code repositories, and compares them to policies stated in the company's contracts and regulations. Continuous source code analysis captures the logic governing data at the code level. Runtime infrastructure monitoring tracks the data flow to live systems. Data is tracked as it is stored and routed to third parties and machine learning algorithms scan regulatory and contractual obligations to compare them to the status of data in the organization. By providing real-time visibility into data flows across the application stack, including microservices and machine learning pipelines, the company says it can enable instant alerts for potential risks. It says it can also reduce the manual effort required in assessing risk by 80%. "It's impossible to keep up with the current state of regulations, especially when GDPR, HIPAA, the EU's AI Act, and a mosaic of local U.S. privacy laws are all different and sometimes at odds," said Co-Founder and Chief Executive Abhi Sharma in a statement. Relyance AI said it increased its enterprise customer base by 30% in the first half of this year and expects to double its annual recurring revenue in 2024. Thomvest Ventures Inc. led the round with participation by Microsoft Corp.'s M12 Ventures Fund, Cheyenne Ventures Management LLC and existing investors Menlo Ventures Management L.P. and Integrity Venture Partners LLC d/b/a Unusual Ventures.

Relyance lands $32M to help companies comply with data regulations | TechCrunch

As the demand for AI surges, AI vendors are devoting greater bandwidth to data security issues. Not only are they being compelled to comply with emerging data privacy regulations (e.g. the EU Data Act), but they're finding themselves under the microscope of clients skeptical about how their data is being used and processed. The trouble is, where it concerns tightening data security practices around AI, many orgs aren't in a position to execute well. According to a survey from BigID, a data control platform, half of organizations rank data security as their top barrier to implementing AI. Hailing from the app engineering and legal sectors, Abhi Sharma and Leila Golchehreh were well-versed in the challenges at play here. Confident they could build something to address the data security conundrum, the pair launched Relyance AI, a platform that checks if a company's data usage is aligned with governance policies. "The concept of how we would build Relyance came to us one evening when we were catching up over pizza in San Francisco," Sharma told TechCrunch. "Although we came from two very different backgrounds, together, we realized that more could be done to ensure visibility in an organization's data processing." Golchehreh is an attorney by trade, having previously served as senior counsel at Workday and autonomous car startup Cruise. Sharma, a software dev, was a platform engineer at AppDynamics before helping to found FogHorn, an edge AI platform that Johnson Controls acquired in 2022. Sharma says that most companies face three main hurdles to AI adoption: a lack of visibility to data in AI, the complexity of how data is handled, and the rapid pace of innovation. All these contribute to reputational risk, Sharma says -- and open companies to legal threats. Relyance's solution is an engine that scans an org's data sources -- such as third-party apps, cloud environments, AI models, and code repositories -- and checks to see if they're in agreement with policies. Relyance creates a "data inventory" and 'data map," which it syncs with customer agreements, global privacy regulations, and compliance frameworks. "Relyance enables organizations to monitor external vendor risks," Sharma said, "while its data lineage feature tracks data flows across applications to identify potential risks proactively." Now, Relyance isn't executing on a totally novel concept. Sharma admits that OneTrust, Transcend, Datagrail, and Securiti AI are among the vendors that compete with it in some way. For example, Datagrail offers automated risk monitoring tools that help companies build third-party app risk assessments quickly. But Relyance appears to be holding its own. Sharma claims that the business is on track to double annual recurring revenue this year, and that Relyance's customer base -- which includes Coinbase, Snowflake, MyFitnessPal, and Plaid -- grew 30% in H1. Setting the stage for further growth, Relyance this month closed a $32 million Series B round led by Thomvest with participation from M12 (Microsoft's venture fund), Cheyenne Ventures, Menlo Ventures, and Unusual Ventures. Bringing the startup's total raised to $59 million, the new funds will be put toward growing Relyance's team to 90 employees by the end of the year. "We decided to raise funds because the demand for AI continues to grow and new privacy and AI regulations are being put into place globally," Sharma said. "Our hiring efforts will primarily focus on expanding our engineering team and increasing our go-to-market capacity to support our product development and growth momentum."