Enterprise Grade Contract AI: Insights from Pramata CEO Praful Saklani

The podcast features a conversation with Praful Saklani, the CEO of Pramata, a company focused on simplifying contract management using AI. Saklani shares his extensive entrepreneurial journey, beginning with his early involvement in the internet world in the mid-1990s after graduating from Swarthmore College with a degree in Economics and Political Science. He describes how he saw the potential of the internet and became a consultant and then an entrepreneur, starting a travel technology company in 1998. He then engaged in impact investing, working on water purification in the Philippines and India. Saklani founded Pramata in 2006 after identifying a need for better contract management solutions, inspired by his experience of seeing lawyers and financial professionals manually reviewing contracts.

Saklani explains that Pramata is focused on helping mid-size to large B2B companies that negotiate contracts extensively, targeting those with revenues from $50 million to over $200 billion. He notes that many companies, even large ones, struggle to keep track of their contracts and the commercial terms within them.

The core of Pramata's approach is to treat contract management as a data problem. Saklani explains that while standardizing contracts is helpful, businesses will always need to negotiate custom deals, meaning that keeping track of the specifics is crucial. Pramata uses AI to create a "contract AI knowledge base", which involves identifying and organizing contracts, extracting key data, and establishing relationships between documents. This knowledge base then powers AI agents that help with contract drafting, risk management, and negotiation, providing insights for sales, legal, and procurement teams. Saklani distinguishes Pramata by its focus on providing enterprise-grade AI that is reliable, accurate, scalable, and secure. He uses the analogy of a microwave, where if you put junk in, you get warm junk out.

Saklani discusses how the accessibility and usability of AI have changed, with people now expecting AI to be easy to use. He points out that while tools like ChatGPT have raised expectations, there's a need for "data grounding," which is ensuring that AI is built on accurate, verified data. He emphasizes that this is particularly important for enterprise clients, where the tolerance for errors is minimal, and that Pramata's focus on accurate data sets the context for more accurate AI-driven results.

When asked about leadership lessons, Saklani stressed the importance of getting ideas in front of customers early and often, viewing the process as an iterative cycle of feedback and adjustment rather than trying to outsmart the market. In addition, he notes the importance of understanding key metrics like net ARR growth, gross retention, net retention, and unit economics . He believes that a focus on these metrics helps companies maintain alignment and understand their performance.

Key Takeaways

• Observe and Identify Real Problems: Saklani's journey began by identifying inefficiencies in contract management during a sale. He recognized a broader pain point, which led to the founding of Pramata.

• Solve Meaningful Problems: Saklani focused on solving a real B2B problem: managing complex contracts and addressing revenue leakage.

• Prioritize Customer Feedback: Saklani emphasizes the importance of early and continuous customer feedback in product development. He believes that entrepreneurs should not "outsmart the market" but rather "collide with the market" and get feedback from actual users.

• Data is Crucial: Saklani learned that accurate and accessible data is at the heart of effective contract management. He views it as a data problem, not just a workflow issue and uses the "g