Executive finance analytics dashboard with predictive litigation cost curves
Litigation FinOps

Turn eDiscovery and Cloud Hosting into a Predictable, Optimized OpEx

Stop letting unstructured data and legacy archival bleed your firm's profitability.

High-Stakes Litigation Demands Massive Data Ingestion. The Costs Shouldn't Be a Black Hole.

High-stakes litigation requires massive data ingestion, but the associated cloud hosting and forensic vendor costs shouldn't be a financial black hole. Firms routinely hemorrhage hundreds of thousands—sometimes millions—on unstructured eDiscovery processing, redundant cloud instances, and legacy data that sits dormant on expensive infrastructure.

Through our proprietary Litigation FinOps methodology, we build predictive financial models that forecast technology costs across the entire litigation lifecycle. We actively audit third-party vendors and restructure heavy infrastructure into scalable operational expenditures—turning your technology budget from a cost center into a strategic asset.

Our approach gives managing partners data-driven visibility into every dollar of technology spend, enabling informed decisions about vendor selection, infrastructure allocation, and case budgeting.

Predictive Cost Modeling

Forecast technology costs across the full litigation lifecycle using historical data and infrastructure benchmarks.

Vendor Audit & Optimization

Comprehensive vendor audits that benchmark costs, eliminate redundancy, and negotiate improved terms.

CapEx to OpEx Restructuring

Transform heavy infrastructure investments into scalable, pay-as-you-go operational expenditures.

$10M+
Total Cost Reductions Delivered

Delivered over $10M in total cost reductions for the firm and class members by optimizing eDiscovery ingestion, cloud hosting, and legacy archival across complex, high-stakes litigation engagements.

Request a Litigation FinOps Assessment

Our team will analyze your firm's eDiscovery, cloud hosting, and vendor spending to identify immediate cost reduction opportunities and build a predictive financial model for your litigation technology portfolio.

Identify 20–40% cost reduction opportunities
Data-driven vendor benchmarking and negotiation
Predictive models for litigation lifecycle budgeting

Request Litigation FinOps Assessment

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Frequently Asked Questions

Litigation FinOps — Executive Q&A

Litigation FinOps applies financial operations principles to the litigation technology lifecycle. It involves building predictive financial models that forecast eDiscovery, cloud hosting, and forensic vendor costs across the entire litigation lifecycle—transforming unpredictable technology spending into a managed, optimized operational expenditure.
Results vary by firm size and litigation volume, but Revive Data Inc. has delivered over $10M in total cost reductions for firms and class members by optimizing eDiscovery ingestion, cloud hosting, and legacy archival. Typical engagements identify 20–40% cost reduction opportunities through vendor consolidation, data tiering, and infrastructure restructuring.
Predictive financial modeling for litigation uses historical spending data, case complexity metrics, and infrastructure benchmarks to forecast technology costs across each phase of litigation. This allows managing partners to budget accurately, negotiate vendor contracts from a position of data-driven leverage, and eliminate budget overruns from unexpected data processing charges.
We conduct comprehensive vendor audits that evaluate pricing structures, service-level agreements, data handling practices, and infrastructure efficiency. We benchmark vendor costs against market rates, identify redundant services, negotiate improved terms, and—where appropriate—recommend alternative solutions that deliver equal or better capability at reduced cost.
Shifting from CapEx (Capital Expenditure) to OpEx (Operational Expenditure) means moving away from large, upfront investments in on-premises infrastructure toward scalable, pay-as-you-go cloud and managed services. For law firms, this reduces financial risk, improves cash flow predictability, and allows technology spending to scale with actual litigation volume rather than projected capacity.