New Covalynt product suite brings scientific rigor and defensible clarity to every stage of the litigation lifecycle

ClaimScore, the legal technology company behind the only data science and AI-driven fraud detection solution for class action settlements, announced that it has rebranded as Covalynt. The new brand reflects the company’s evolution from a single anti-fraud product into a full-service data science platform purpose-built for complex litigation.

Under the Covalynt name, the company now offers an integrated suite of products—ClassResolution, DeepValidation, ClaimScore by Covalynt, and Bespoke Data Solutions—designed to solve the most difficult data problems in high-stakes cases, from early discovery through settlement distribution.

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“Complex litigation has become fundamentally data-driven, but the industry hasn’t kept pace with the data-science rigor these matters now require,” said Don Beshada, CEO and co-founder of Covalynt. “ClaimScore showed us that fraud detection was just one piece of a much larger problem: fragmented class records, unreliable notice data, and identity-resolution challenges that traditional tools simply can’t handle. Covalynt is our answer to that broader mandate—the bond between complex litigation and data science.”

Originally launched as ClaimScore, the company pioneered bank-level, data-driven backend fraud analysis to help settlement administrators, attorneys and companies detect and prevent sophisticated class action claim fraud in real time.

“Our clients started coming to us with questions that went far beyond ‘Is this claim fraudulent?'” said Bryan Heller, co-founder of Covalynt. “They needed defensible class datasets, reliable notice strategies, and transparent models that could survive legal challenges. Covalynt’s platform is built to meet that reality—engineered by data scientists, proven in high-profile cases, and designed to stand up under expert and judicial scrutiny.”

Covalynt’s platform now includes four core offerings that bring scientific structure and defensibility to the entire litigation lifecycle:

• ClassResolution – Guides discovery toward the data that matters and builds a unified, audit-ready class dataset. Covalynt helps legal teams request the right fields, reconcile fragmented records across sources, and apply engineered identity-resolution methods so that class membership can be defended under intense judicial and expert scrutiny.
• DeepValidation – Transforms incomplete or inconsistent class contact data into actionable intelligence. DeepValidation enriches and validates addresses, emails, and other contact points, maximizing direct deliverability and sharpening indirect notice strategies while documenting each step in a reproducible, transparent process.
• ClaimScore – Retains and extends the original ClaimScore fraud-detection capabilities. The product uses multi-factor, AI-driven scoring to identify fraudulent or suspicious claims—including synthetic identities and phone-farm submissions—while preserving legitimate claims and providing objective, evidence-backed documentation to courts and settlement stakeholders.
• Bespoke Data Solutions – For challenges that don’t fit a standard pattern, Covalynt builds custom engineered workflows and applied data science solutions tailored to the specific facts, systems, and risks of a case. These bespoke engagements address root-cause data issues—such as complex identity graphs, multi-defendant data feeds, or unusual notice channels.

Covalynt’s methodology has been deployed in a wide range of privacy, consumer, and antitrust matters, including federal and state cases involving some of the world’s largest technology, data, and consumer brands. The company’s tools and testimony have been used in cases such as Lopez v. Apple, Inc., Katz-Lacabe et al. v. Oracle America, Inc., Mackmin et al. v. Visa Inc. et al., and Frasco v. Flo Health, Inc., Google LLC, and Meta Platforms, Inc., among others.

Across these matters, Covalynt’s role has expanded from fraud detection and claim validation to broader responsibilities such as class data engineering, notice optimization, and ongoing analytics that support negotiations, fee petitions, and post-distribution reporting.

“We built Covalynt for the data reality of modern cases,” Beshada added. “That means transparent, reproducible logic, rigorous security, and solutions that make litigation fairer and more efficient for courts, class members, and counsel on all sides.”