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This case study details the development of the Immigration Financial Tool (IFT), a sophisticated digital platform designed for the law firm Ogletree Deakins. The project aimed to replace a fragmented legacy system with an AI-enabled solution that automates complex billing, fee scheduling, and financial forecasting. By centralising data from various legal and financial tools, the new system addresses critical issues such as manual data entry errors, security vulnerabilities, and inefficient reporting. The narrative highlights a user-centred design processthat prioritised high-impact features, including automated audit trails and scenario-based predictive modeling for client spends. Ultimately, the transition resulted in significantly improved operational accuracy, enhanced regulatory compliance, and a substantial reduction in administrative man-hours.


  • How did automation cut billing errors across thousands of cases?
  • How does forecasting manage uncertainty and client-specific timing?
  • What trade-offs balanced efficiency with compliance and ethical AI?



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CLIENT • 
Ogletree Deakins
CATEGORY • 
PRODUCT & SYSTEMS DESIGN
DATE • 
4 February 2026

Immigration financial tool

Ogletree Deakins one of the US's largest immigration law firms was running critical billing and forecasting operations on a fragmented system held together by manual effort and institutional memory. Attorneys were losing billable hours to administrative reconciliation. Errors compounded across thousands of cases. IFT was designed to fix the cognitive architecture of that problem not just automate the workflow.

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