{"version":"1.0","type":"rich","provider_name":"Acast","provider_url":"https://acast.com","height":250,"width":700,"html":"<iframe src=\"https://embed.acast.com/$/6683eb5ce091a56d49596947/690b5b1cb27ff20ceb150cc0?\" frameBorder=\"0\" width=\"700\" height=\"250\"></iframe>","title":"Building the Legal Stack: Retrieval, Context, and Real-World ROI, with Nitish Mutha, Co-founder & CTO of Genie AI","thumbnail_width":200,"thumbnail_height":200,"thumbnail_url":"https://open-images.acast.com/shows/6683eb5ce091a56d49596947/1762350425155-9ce227ac-8668-4a41-a804-d9db5562bb6e.jpeg?height=200","description":"<p>In this episode of <em>The Vertical SaaS Podcast</em>, <strong>Gavin Savage</strong> sits down with <strong>Nitish Mutha</strong>, Co-founder and CTO of <strong>Genie AI</strong>, to unpack how the company is building the next generation of legal infrastructure, a true <em>agentic</em> legal stack that combines retrieval, reasoning, and trust.</p><p><br></p><p>Nitish shares his journey from engineer to founder, and how Genie evolved from a two-person experiment in Barclays Ventures’ Eagle Labs to one of the UK’s most ambitious AI startups. He discusses how LLMs transformed Genie’s speed of innovation, why retrieval and context are core to reliability, and how the team defines real-world ROI in a market crowded with hype.\t</p><p><br></p><p>The conversation dives deep into product-led growth, defensibility in vertical AI, hiring for adaptability, and how Genie is creating the foundation for a world where AI handles not just contracts but legal reasoning itself.</p><p><br></p><h3>`Takeaways</h3><ul><li>Nitish’s engineering background shaped Genie’s product philosophy and technical depth.</li><li>Genie AI evolved from serving lawyers to empowering business users and teams.</li><li>Retrieval, context, and reliability are at the heart of Genie’s legal reasoning engine.</li><li>The rise of LLMs unlocked Genie’s product velocity and scale.</li><li>The company’s 7-year R&amp;D head start led to a £13.3M Series A from GV and Khosla.</li><li>Product-led growth remains key to sustained adoption in legal AI.</li><li>Hiring centers on curiosity, adaptability, and ownership.</li><li>Trust, defensibility, and measurable ROI define success in legal AI.</li><li>The legal industry is shifting from manual workflows to intelligent systems.</li><li>Genie AI’s long-term vision: the core legal stack for modern businesses.</li></ul><h3><br></h3><h3>Chapters</h3><p> 00:00 – Introduction to Genie AI and Nitish’s background</p><p> 02:39 – Early challenges and the first product iterations</p><p> 05:24 – Shifting focus from lawyers to business users</p><p> 08:20 – The impact of LLMs on product speed and accuracy</p><p> 11:26 – Finding early market validation</p><p> 14:02 – The funding journey: from bootstrap to GV and Khosla</p><p> 17:08 – Product-led growth and differentiation in legal AI</p><p> 20:08 – Driving adoption and defining ROI</p><p> 22:50 – Advice for building vertical AI products</p><p> 24:11 – Reliability, hallucinations, and real-world guardrails</p><p> 29:07 – Ensuring quality and trust in AI systems</p><p> 31:30 – Inside Genie’s technical stack: retrieval and reasoning</p><p> 38:33 – Scaling post-LLM: product, team, and culture</p><p> 43:26 – Hiring and leadership in an AI-first startup</p><p> 46:25 – The future of agentic legal and Genie’s long-term vision</p><p><br></p><h3>Keywords</h3><p>Genie.ai, Legal Tech, Artificial Intelligence, LLMs, Agentic AI, Contract Management, Startup Funding, Product-Led Growth, Hiring Strategies, Legal Automation, Technology Innovation</p>","author_name":"Gavin Savage"}