Companies are increasingly facing challenges in transitioning from pilot tests of artificial intelligence to reliable systems in their daily operations. In this context, Pramaana Labs emerges as a new venture aimed at solving the reliability problem by combining mathematical formalization tools with the power of language models.
The company announced a seed funding round of $27 million led by Khosla Ventures, with participation from Accel, BoldCap, Nexus Venture Partners, Premji Invest, and Unbound. This backing comes at a time when reliability has become a priority for implementing AI in real-world environments.
Focus on high-sensitivity verticals
Pramaana will concentrate on particularly sensitive areas such as law, drug discovery, and tax preparation. In these fields, a mistake can incur high costs, and the highest level of reliability is required. Implementing AI in these systems necessitates more robust protections against hallucinations and failures.
According to Ranjan Rajagopalan, co-founder and CEO of the company, these domains lend themselves well to formalization. “It’s like mathematics in the sense that there are many rules that must be followed,” he explained, referring to the tax code. Once those rules are codified, the reasoning becomes deterministic.
Pramaana's system uses a conventional LLM to maintain flexibility and respond to natural language questions or solve complex problems. However, it incorporates a deterministic layer that verifies the model's work.
