ClassResolution by Covalynt

Clarity at the heart of class certification.

Transform early-stage discovery into actionable strategy. We illuminate data potential to help you visualize the class early, creating defensible, audit-ready definitions built on a unified, scientific foundation.

Book a demo

Establish a defensible, audit-ready foundation for class certification arguments.

The Litigation Challenge

Class data rarely arrives clean. Limited visibility into what data exists makes discovery requests difficult to navigate, and even when the right fields are obtained, fragmented records, inconsistent identifiers, and complex variables make it nearly impossible to define a class with the precision required for certification and damages modeling.

The Covalynt Solution

We bring order to chaos by guiding discovery toward the right data and scientifically validating and resolving identities. Our process unifies disparate records into a clear, consistent dataset that withstands scrutiny from opposing experts and courts.

Discovery Guidance

Identify essential data fields, anticipate limitations, and align requests with case objectives.

Permutation Inventorying

Map every data pattern, isolate edge cases, and surface gaps that impact class definition.

Data Structuring & Normalization

Standardize formats, repair inconsistencies, and create uniform inputs for downstream analysis.

Source-Level Enrichment

Enhance raw fields, fill contextual gaps, and elevate low-quality data to analytical readiness.

Cross-Temporal Record Linkage

Connect shifting identifiers, reconcile historical changes, and track entities reliably over time.

Identity Resolution

Unify disparate records, dedupe overlapping entities, and establish a single source of truth.

Your Partner in Every Step of Success

Discover how our expertise has driven success in 50+ cases, providing valuable insights and answers.

Our Experience

A Data privacy case being resolved in the Northern District of California

The case involved over 15 million inconsistent, fragmented records. Covalynt enriched this data using first and third-party sources, then standardized and cleaned it. We employed Levenshtein distances for fuzzy matching and triangulation to resolve each record to a specific identity. This process successfully identified individuals within the California sub-class during the class period.