We’ve evolved beyond fraud detection; offering a full-suite of data science driven products to aid in the modernization of Complex Litigation.
Data-driven, backend claim analysis, in real-time.
Bulk review claims using data-driven backend analysis via file transfer.
Aggregated results from a data-driven backend analysis to gain case insights
Aggregated results from a data-driven backend analysis to gain case insights
When defendant data is incomplete, every downstream metric is at risk. We fill in the gaps and apply proper deduplication — giving your class definition a defensible foundation.
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Class data rarely arrives clean. Fragmented records, duplicate identities, and inconsistent fields make it nearly impossible to define a class with the precision required for certification arguments, damages modeling, and judicial scrutiny.
We guide discovery toward the right data, enrich incomplete records with proprietary sources, and resolve every identity into a single, unified dataset, ensuring proper deduplication, built to withstand opposing experts and court review.
Identify essential data fields, anticipate limitations, and align requests with case objectives.
Map every data pattern, isolate edge cases, and surface gaps that impact class definition.
Standardize formats, repair inconsistencies, and create uniform inputs for downstream analysis.
Enhance raw fields, fill contextual gaps, and elevate low-quality data to analytical readiness.
Connect shifting identifiers, reconcile historical changes, and track entities reliably over time.
Unify disparate records, dedupe overlapping entities, and establish a single source of truth.
Discover how our expertise has driven success in 50+ cases, providing valuable insights and answers.
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.
