Anurag Shukla

Today, I'm thrilled to announce Pramaana's $27M seed, led by @khoslaventures. The foundational domains that hold the world together: tax, law, finance, healthcare; all run on certainty. Probabilistic AI can't give them that. We’ve been asked to accept wrong answers with AI as ‘hallucinations’, while in traditional software terms, it’s just a bug. And a wrong answer in such mission-critical domains is more than just a bug, it's a liability that could have catastrophic impact. We built Pramaana to deliver a 100% trustable experience to the domains that run on certainty: AI that is provably correct, not probabilistically correct. We turn statute and regulation into machine-verifiable code, so every output ships with mathematical proof of correctness. Our mission is to make AI take ownership of it’s work. Pramaana in Sanskrit stands for “means of valid knowledge”, and we’re going to achieve that by formalizing the world’s knowledge.

@vkhosla This is exactly the frontier founders should be building for. AI is getting very good at fluency. But companies do not run on fluency. Companies run on trust, rules, hierarchy, approvals, accountability, memory, risk control, and proof. The next critical layer is not simply “more generative AI.” It is verifiable AI inside real organizations. Because the hard problem is no longer: “Can AI produce an answer?” The hard problem is: Can the company trust it? Can the source be verified? Can the decision be defended later? Can the right person approve it? Can sensitive data stay within the right boundary? Can the system understand who has authority? Can it respect what must never be done? Can it operate according to the company’s culture, rules, goals, and risk appetite? Can every critical action leave an audit trail? This is where traditional software fails. This is where generic productivity AI fails. And this is where uncontrolled AI agent layers will become a liability for millions of businesses. For large enterprises, this is a governance challenge. For SMEs, it is an existential infrastructure gap. There are hundreds of millions of businesses that cannot build their own AI governance stack. They cannot manage scattered AI tools, disconnected assistants, risky automations, fragmented permissions, and unverified outputs. They need a governed company work layer. A layer where AI does not just generate. It prepares, checks, routes, explains, verifies, and escalates. It understands the company structure. It knows roles, departments, authority levels, approval paths, restricted actions, and visibility rules. It helps the business move faster — without removing human control from critical moments. That is why we are building Orygent. Not another chatbot. Not another generic automation product. Not another unmanaged AI agent stack. Orygent is built for companies that need AI work to be controlled, traceable, approval-aware, and defensible. With Atlas and role-based digital work companions, a company can coordinate finance, operations, sales, compliance, support, services, and management work through a governed layer — while keeping leadership, approval, audit, and trust at the center. The next wave of AI adoption will not be won by the companies using the most AI. It will be won by the companies that can verify, govern, and defend how AI works inside the business. That is the real frontier. orygent.com