Terabytes of discovery. Thousands of plaintiffs. One unified view.

Overstand is built for volume. It ingests and processes terabytes of discovery data — employment records, financial documents, communications, contracts, medical records — and normalizes everything into a unified evidence foundation. The platform scales horizontally, so processing 10 million documents takes the same workflow as processing 10,000.

Overstand supports any class action where establishing commonality across plaintiffs requires large-scale data analysis: employment discrimination, wage and hour violations, consumer fraud, product liability, securities fraud, data breach litigation, and environmental contamination cases. Any matter where patterns across class members are the key to certification.

Overstand analyzes records across all putative class members to identify shared facts, common policies, and uniform practices. It detects patterns — like a company-wide policy applied discriminatorily or systematic wage underpayment — that demonstrate questions of law or fact common to the class, satisfying Rule 23(a)(2).

Yes. Overstand processes financial records, pay stubs, billing data, medical records, and other damages-relevant documents across the entire class. It calculates individual and aggregate damages, identifies outliers, and generates structured damages models that are defensible and traceable to source records.

Traditional e-discovery platforms handle document collection, processing, and hosting — they organize documents for human review. Overstand is built for something different: high-scale, end-to-end evidence pipelining for large-scale class actions. When you have terabytes of discovery data across thousands of plaintiffs, Overstand processes it all, detects commonality patterns, quantifies damages, and delivers structured certification evidence. We're built for the cases where the data volume itself is the challenge.

Overstand normalizes documents across all formats — PDFs, spreadsheets, emails, scanned records, database exports, and structured data files — into a unified schema. This means employment records from different HR systems, pay stubs in different formats, and medical records from different providers are all analyzed together as a single dataset.

Yes. Overstand generates structured evidence packages aligned with Rule 23 requirements: numerosity analysis, commonality evidence with specific shared facts, typicality assessments comparing named plaintiffs to the class, and adequacy documentation. Every finding includes full source attribution for citation in briefs and declarations.

Processing time scales with data volume, but Overstand typically processes millions of records in hours, not months. A typical employment class action with 500,000 employment records and 2 million communications can have initial commonality analysis and damages estimates within a day of ingestion.

Every pattern, damages calculation, and commonality finding includes full source attribution — the specific document, record type, class member, date, and data field. Attorneys can verify every claim against original records, ensuring the analysis is defensible and court-ready.

Overstand processes all data within secure, isolated environments. Class member personally identifiable information is handled in compliance with applicable privacy requirements. Data is never shared across matters or clients, and the platform supports anonymization and redaction workflows required for class action proceedings.