Photo credit: venturebeat.com
Relyance AI, a provider of a data governance platform, has recently unveiled a new solution designed to tackle a major issue in the adoption of AI within enterprises — the challenge of tracking data movement in complex systems. This announcement follows their successful acquisition of $32.1 million in Series B funding last October.
The newly launched Data Journeys platform provides organizations with critical insights into how data is utilized, addressing a significant gap for those implementing AI by shedding light on not only where data resides but also its journey through various applications and third-party services.
CEO and co-founder Abhi Sharma emphasized in an interview with VentureBeat that the platform delivers a “context-aware, visual representation of the data journey,” enabling businesses to understand the underlying reasons for data processing. This foundational clarity is essential for effective AI governance.
As enterprises ramp up their AI efforts, the need for robust governance frameworks has become increasingly urgent. Regulatory pressures are rising globally, with more than a quarter of Fortune 500 firms noting AI regulation as a concern in SEC filings. Additionally, fines related to GDPR reached approximately €1.2 billion (around $1.26 billion) in 2024 alone, highlighting the financial stakes involved.
How Data Journeys tracks information flow where others fall short
Data Journeys signifies a notable advancement over traditional data lineage methods, which primarily track data movement within specific systems on a table-to-table or column-to-column basis.
Sharma explained that current lineage practices often limit visibility to data movements confined within platforms like Snowflake or S3. Key questions about the original sources of data, the transformations it underwent, and the role of third-party APIs remain unanswered. Data Journeys aims to bridge this gap by offering a comprehensive overview of the complete data lifecycle, from initial collection to various transformations and applications. The system begins with code analysis to provide context surrounding the data processing methodologies employed.
Lawrence Schoeb, the Senior Director and Data Protection Officer at Samsara, noted that these automated capabilities are pivotal for their global AI governance framework, addressing key operational challenges.
Four business problems that data visibility promises to solve
Sharma outlined four primary areas where Data Journeys offers significant value:
First, it enhances compliance and risk management. “Organizations are often required to ensure data processing integrity, yet they lack internal visibility — a form of blind governance,” he stated. The platform equips businesses to robustly justify their data handling practices under regulatory scrutiny.
Second, it aids in bias detection. Companies can now trace potential biases back to their sources rather than simply evaluating the immediate training dataset. Sharma highlighted that biases may emerge at inference stages, meaning it is crucial to understand the full data journey.
Third, a focus on explainability and accountability for high-stakes decisions becomes crucial. Data Journeys enables firms to deduce the reasons behind AI outcomes, an essential step for ensuring proper model behavior.
Lastly, the platform serves regulatory compliance needs by offering “mathematical proof points” that demonstrate appropriate data usage, guiding companies through a landscape of complex regulations.
From hours to minutes: Measurable returns on better data oversight
Relyance asserts that the platform brings about notable returns on investments, with users reportedly experiencing a 70-80% decrease in the time spent on compliance documentation and evidence collection. The time required to ascertain the usage of specific data has dramatically shifted from hours to mere minutes.
Sharma recounted a case where a direct-to-consumer organization transitioning payment processors from Braintree to Stripe inadvertently stored sensitive information in plaintext due to a code error that could have gone unnoticed without the platform’s oversight.
Keeping sensitive data inside your walls: The self-hosted option
In conjunction with Data Journeys, Relyance is also launching InHost, a deployment model that allows organizations with stringent data sovereignty requirements to host the platform on their own infrastructure. This option caters particularly to highly regulated sectors such as FinTech and healthcare.
Sharma noted that industries like banking, fraud detection, and personal healthcare services are particularly keen on this option, as it helps mitigate concerns regarding sensitive data leaving the organization’s control.
Relyance AI’s expansion plans point to growing AI governance market
Relyance is strategically positioning Data Journeys within a broader goal of establishing a unified AI-native platform that facilitates global privacy compliance, data security management, and comprehensive AI governance.
Sharma highlighted plans to launch an extensive AI governance solution in the latter half of the year, which will encompass compliance management, real-time ethics oversight, bias detection, and accountability for both third-party and internal AI systems.
The company’s long-term ambitions are robust. “AI agents are slated to control many aspects of the world, and we aim to be the company that offers the necessary infrastructure for organizations to trust and manage these systems effectively,” Sharma remarked, underscoring a commitment to elevating the global data utility index.
Investors bet big on data governance as competition heats up
Relyance faces competition from established firms within the data governance realm. In previous discussions, Sharma acknowledged competitors such as OneTrust, Transcend, DataGrail, and Securiti AI, but expressed confidence that Relyance’s integrated approach offers a distinctive advantage.
Investor sentiment remains positive, exemplified by the company’s recent $32.1 million Series B fundraising, led by Thomvest Ventures alongside participation from Microsoft’s M12 Ventures Fund, contributing to a total of $59 million raised.
Umesh Padval, Managing Director at Thomvest Ventures, emphasized the urgency in resolving the challenges Relyance addresses, stating, “Relyance AI empowers Chief Privacy, Security, and Information Officers to effectively manage data privacy and compliance, minimizing potential penalties while fostering responsible AI adoption.”
Why data oversight might determine AI success in the enterprise
Sharma articulated the importance of data oversight as a foundational element for any organization implementing AI technologies.
“AI has emerged as a central priority for organizations, and understanding the mechanisms behind trust and governance is essential,” he explained.
“Regardless of whether organizations opt for Relyance or another solution, the ability to achieve clarity in data oversight is vital, as it significantly influences the pace and success of AI integration.”
As enterprises are compelled to enhance their AI capabilities, maintaining insight into data processes has become paramount, evolving from a compliance requirement to a strategic business necessity. This transformation points towards a sizable paradigm shift in industries, where those cultivating visibility tools act as the critical infrastructure supporting responsible AI, much like air traffic control systems ensure safe operations in the skies. Without such systems, even the most sophisticated algorithms risk becoming liabilities rather than assets.
Source
venturebeat.com