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Advisory Board

LegalDeskAI is shaped by a founder who codes and an advisory board of practicing professionals — from AI research and analytics to scalable systems. They help ensure MAYA and SMRITI stay grounded in real practice, not just demos.

Founder

Kunjan Dalal

Kunjan Dalal

Founder

Software engineer since 2008 and LL.B. graduate, building a privacy-first AI platform for Indian lawyers.

Tirth Pandya

Advisor

Tirth Pandya

Technical Advisor — AI Research & Predictive Systems (Waymo, Ex-Lyft, Ex-Microsoft)

Tirth is a Staff Software Engineer at Waymo (Google's self-driving division) with deep expertise in machine learning, behavior prediction, trajectory estimation, and safety-critical AI systems. Previously at Lyft Level-5 Autonomous Driving, Microsoft, and Intel, he has contributed to large-scale AI that powers real-world vehicles and decision systems. With patents in robotics frameworks, prediction systems, and high-throughput ML architectures, Tirth brings cutting-edge research thinking to Legal Desk AI — particularly in judgement prediction models, case trajectory forecasting, anomaly detection in legal drafting, and risk scoring frameworks. At Legal Desk AI, his advisory role strengthens our long-term AI research vision: from drafting automation → to predictive justice intelligence.

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Advisory board

Advisor (legal clearance in progress)

Legal clearance in progress.

Aniesh Chawla

Advisor

Aniesh Chawla

Technical Advisor — AI Systems & Scalable Infrastructure (Google, Ex-Tesla)

Aniesh is a Software Engineer at Google with experience building large-scale backend systems, AI-powered applications, and production ML infrastructure. His work includes deploying LLM-powered chat systems, architecting microservices at scale, and improving reliability and performance for millions of users. Previously, he has worked with Tesla, Google Fiber, and research teams across AI, networking, and distributed systems. At Legal Desk AI, Aniesh advises on AI system architecture, scalable infrastructure, and production-grade deployment of intelligent systems, helping ensure our platform is built for real-world usage and long-term scale.

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