privacy-preserving-ai
(3)
Ajit Tharaken
Ajit Tharaken is the CEO of Consilient, a Washington, D.C. fintech building federated-learning AI to catch financial crime without ever moving a bank's data. A Columbia-trained computer scientist, he previously ran Opus Global (Alacra) through its sale to NICE Actimize, then led NICE Actimize's Data Intelligence business. He pitches a blunt thesis: the global anti-money-laundering system is outdated, and the fix is letting institutions train AI models locally and share the intelligence, not the data.
Matthew Wang
Matthew Wang is the founder and CEO of OpenGradient, a New York company building a decentralized compute layer for verifiable and confidential AI. A former Two Sigma research engineer who cut his teeth on equity-options market-making infrastructure, he left quant finance in 2024 to chase a simpler question: can you prove that the AI answering you is the AI you think it is? OpenGradient runs models on-chain with cryptographic proofs and hardware enclaves, and has raised $9.5M led by a16z crypto, with backing from Coinbase Ventures, SV Angel, and angels including Balaji Srinivasan, Illia Polosukhin, and Sandeep Nailwal.
Vaikkunth Mugunthan
Vaikkunth Mugunthan is the co-founder and CEO of Dynamo AI, a San Francisco company that builds privacy, security, and compliance guardrails for enterprise generative AI. An MIT PhD in computer science with a Harvard minor in privacy, fairness, and law, he turned years of federated-learning and differential-privacy research into a venture-backed startup serving Fortune 500 firms in finance, insurance, electronics, and automotive. He was named to Forbes 30 Under 30 Asia 2025, captained MIT's cricket team, plays the violin, and has traveled to 16 countries.