Adalat AI: Justice at Scale

By Zack Doherty, Russell Siegelman, Laura Hattendorf
2026 | Case No. E953 | Length 15 pgs.
The case follows Utkarsh Saxena and Arghya Bhattacharya, cofounders of Adalat AI, as they build and scale an AI-enabled system designed to address judicial backlogs in India’s courts. Operating in a developing economy with constrained public budgets, uneven digital infrastructure, and evolving regulatory norms, Adalat AI partners with high courts to automate transcription and improve case flow. As adoption expands, the founders confront strategic choices about organizational form and growth: whether to remain a nonprofit aligned closely with government institutions, pursue a for-profit or hybrid structure to access growth capital, or spin out commercial applications such as analytics and licensing. The case examines tradeoffs between mission alignment and financial sustainability, the challenges of scaling AI in public-sector environments, and the broader question of how entrepreneurs can build durable ventures within developing entrepreneurial ecosystems.

Learning Objective

Students will learn to evaluate strategic tradeoffs in building AI ventures within public-sector and developing-economy contexts, including decisions around nonprofit versus for-profit structures, partnership models with government institutions, and long-term revenue design. They will analyze how founders assess ecosystem constraints—such as limited growth capital, regulatory complexity, compute costs, and talent scarcity—when scaling mission-driven technology. Students will examine how leadership balances trust, impact, and financial sustainability while positioning an AI-enabled venture for durable growth in an evolving entrepreneurial ecosystem.
This material is available for download by current Stanford GSB students, faculty, and staff, as well as Stanford GSB alumni. For inquires, contact the Case Writing Office. Download