The startup said it will use the capital to train its formalisation and prover models, expand its AI research team and onboard domain experts across regulated sectors such as taxation, healthcare diagnostics, cybersecurity and financial compliance.
“AI has an accountability gap,” said Ranjan Rajagopalan, co-founder and chief executive officer of Pramaana Labs. “Many of the world’s hardest problems are not unsolvable; they are unformalised. Every domain where mistakes can affect health, money or freedom is governed by rules. Pramaana encodes those rules into a form that machines can reason over with certainty.”
The company’s early backers include Pushmeet Kohli, vice-president at Google DeepMind, and Sriram Rajamani, corporate vice-president at Microsoft CoreAI, both recognised for their work in formal verification.
Pramaana’s platform converts domain-specific knowledge into machine-verifiable outputs. The system first translates rules and regulations—such as tax codes, clinical protocols and financial compliance frameworks—into a formal language that machines can process. User queries are then translated into formal statements and checked through a proof engine before an answer is returned.
According to the company, the system either provides a machine-checkable proof supporting the answer or identifies the specific rule that prevents a valid conclusion. The platform is designed to withhold responses when proof cannot be established.
“We backed Pramaana at the earliest stage because we believe the team is addressing one of the most important challenges in AI — trust,” said Sathya Nellore Sampat, General Partner, BoldCap. “Auto-formalisation infrastructure has the potential to become a critical building block for future AI systems.”
Pramaana said its research ecosystem includes collaborations with academics from IIT Delhi, IIT Madras, UC Berkeley and Stanford University’s Centaur Lab. Its tax formalisation efforts are advised by former US Internal Revenue Service Commissioner Danny Werfel and supported by researchers from Yale Law School and Stanford.
The founding team combines expertise in formal methods and large-scale AI systems. Rajagopalan previously led Google Maps Moderation, while co-founder Krishnan Raghavan worked on Glean Assistant at enterprise search company Glean. Sanjay Ganapathy, formerly a staff research engineer at Google DeepMind, contributed to the Gemini family of AI models. All three founders are alumni of IIT Madras.
 "investment, funds, funding")