Thousands of Claims. One Coherent Narrative.
Class action fraud cases collapse under their own weight. The Supreme Court now requires damages methodology matching the specific theory of harm for which the class is certified. Mere allegations of systemic violations won't satisfy Rule 23(a). Vipernauts aggregates thousands of individual claims into statistically defensible patterns, traces common fund flows, and produces the class-wide evidence that certification demands.
Pain Points We Solve
Scale Without Structure
Thousands of individual claims arrive in different formats, from different jurisdictions, with varying documentation quality. Digital evidence has replaced paper as the primary source — but without automated structuring, the volume buries the very pattern that proves the class exists.
Proving Commonality
Courts have become more rigorous: mere allegations of systemic violations won't satisfy Rule 23(a). Plaintiffs must demonstrate a specific, identifiable harm caused by a common mechanism — and the evidence must be class-wide, not anecdotal. Pattern analysis at this scale exceeds manual capability.
Tracing Aggregate Fund Flows
Individual losses are small. Aggregate losses are massive. Tracing how funds moved from thousands of victims through layered intermediaries — traditional banking, crypto bridges, shell entities — to common beneficiaries requires forensic infrastructure most litigation teams lack.
Damages Quantification
The Supreme Court has raised the bar: damages methodology must match the specific theory of harm for which the class is certified. Generalized models that encompass rejected theories are now insufficient. Plaintiffs need calculations that survive judicial scrutiny and opposing expert challenge simultaneously.
Platform Capabilities
Automated Claim Aggregation
Ingest thousands of individual victim reports and structure them into consistent, comparable records — extracting entities, dates, amounts, and relationships automatically.
Pattern Recognition at Scale
Behavioral analysis across the entire class identifies the common scheme, common actors, and common mechanisms that establish commonality for certification.
Aggregate Fund Tracing
Follow money from thousands of individual victims through intermediaries to common endpoints — building the financial map that proves coordinated extraction.
Class-Wide Evidence Packages
Generate court-ready exhibits that demonstrate systemic harm with statistical rigor — damages models, pattern summaries, and representative case analyses formatted for class certification and trial.
Key Capabilities
Statistical Damages Modeling
Defensible damages calculations across the entire class, with configurable methodologies and sensitivity analysis for opposing expert challenges.
Commonality Analysis
Automated identification of common questions of fact and law across victim claims, supporting class certification motions with quantitative evidence.
Representative Sampling
Statistically valid sampling frameworks that allow detailed analysis of representative claims to support conclusions about the entire class.
Settlement Administration Support
Structured claim data and damages calculations ready for distribution modeling when cases resolve through settlement.
Multi-Defendant Attribution
When multiple defendants are involved, trace which entity harmed which class members and quantify proportional liability.
Expert Report Generation
Automated drafting of expert report frameworks with supporting data, statistical summaries, and methodology documentation.