Pramaana Labs Secures $27M Seed Funding to Build Reliable AI Verification Technology

As businesses increasingly move AI from pilot projects into real-world operations, ensuring reliability has become a major challenge. Pramaana Labs aims to address that issue by combining the flexibility of large language models (LLMs) with the precision of mathematical formal verification.

On Wednesday, the startup announced a $27 million seed funding round led by Khosla Ventures, with participation from Accel, BoldCap, Nexus Venture Partners, Premji Invest, and Unbound.

Pramaana plans to focus on industries where accuracy is critical, including legal services, drug discovery, and tax preparation. In these sectors, even small AI mistakes can have significant financial, legal, or healthcare consequences, making dependable verification essential.

Co-founder and CEO Ranjan Rajagopalan believes these highly regulated fields are particularly well-suited to formal verification because they operate under clearly defined rules.

“It’s like math in the sense that you have a lot of rules that you need to abide by,” Rajagopalan said while referring to tax regulations. “Once you have a codified version of it, the reasoning on top of it starts becoming deterministic.”

Rather than replacing large language models, Pramaana’s platform adds a deterministic verification layer that checks AI-generated outputs before delivery. The LLM continues to handle natural-language interactions and complex reasoning, while the verification system ensures that responses comply with predefined rules.

The company’s approach is based on formal verification techniques using the open-source LEAN programming language, which is widely used for mathematical proof verifications. Rajagopalan pointed to France’s CATALA project as an example of how tax laws and government regulations can be translated into executable, verifiable code.

For each industry it serves, Pramaana intends to build dedicated LEAN-style verification frameworks, guided by subject-matter experts. Its tax platform is being developed with former IRS Commissioner Danny Werfel, while professors from IIT Delhi, IIT Madras, and the University of California, Berkeley are contributing to systems focused on cybersecurity and drug discovery.

“The world’s hardest problems are not unsolvable. They are informalized,” Rajagopalan said. “Every domain where being wrong can cost someone their health, money, or freedom has rules.”

Pramaana’s goal is to convert those complex rule sets into verifiable systems, helping enterprises deploy AI with greater confidence in environments where precision and trust are essential.