“AI doesn’t just hold up a mirror to your mistakes. It amplifies them.”

Sandhya Ramachandran, CTO of Wipro, makes the case that most enterprises are thinking about AI backwards - as a tool to deploy, not an ecosystem to redesign around.

Our very own Sujit Janardanan digs into a real healthcare claims case study (one expert processes 40 claims an hour, a newcomer takes six months to reach four), her 'AI first, human-centric' philosophy, and a rapid-fire round where she has to call keep, delegate, or escalate on real high-stakes decisions.

A grounded, thought-provoking conversation for anyone past the pilot stage.

The moment your data enters an AI workflow, your existing security controls don’t get bypassed - they evaporate.

Amar Kanagaraj, founder of Protecto, makes the case for an independent trust layer built for the AI era covering a Middle Eastern bank that can’t let data leave the country, a healthcare company whose real risk was never the model, and an AI built to understand “salary information” as a concept, not just a pattern.

His core analogy: brakes don’t slow a Ferrari down. They’re what let it go fast.

“This is scary good." - That's what a healthcare client's own security team said on a call, watching an AI agent book appointments and resolve scheduling conflicts inside their regulated clinical software.

Rakesh Vaddadi, CEO of Beacon.li, tells host Sujit Janardanan how his team builds AI agents that don't just answer questions about enterprise software - they operate it, with zero backend integration and a knowledge graph learned straight from the UI.

Also: the claim that Beacon beat OpenAI to a multi-agent orchestrator by six months, and a rapid-fire round on exactly which tasks Rakesh does (and doesn't) trust an AI agent to handle alone.

Six thousand images a day with zero room for error!

Girish Vadharajan, Chief Data and AI Officer at Innoviti, built the AI system verifying field agents' proof of work across thousands of payment terminals nationwide - and it broke every assumption a standard LLM API prototype makes.

Karan Kirpalani gets into the black-on-black detection problem, the checkbox that made a top-tier model hallucinate, and a case study of a client cutting their monthly AI bill from roughly 80,000 dollars to a flat 9,000.

A real production build story, you cannot afford to miss as a builder.

A bank spent $60 million on a core system migration. It failed and shipped nothing.

Aravind Jayendran, Co-founder of Latentforce, is betting the opposite way - an AI built to do one thing, code migration, with enough precision to touch a 20-year-old ERP system that nobody at the company fully understands anymore.

Plus: why your code is your IP, and why that changes everything about which AI you trust with it.

Tune in to the complete episode to dive into his approach.

You're worried about latency, model quality, and fundraising.

You should also be worried about export controls, GPU choke points, and the single executive order that could rewrite your entire roadmap.

Pranay Kotasthane (Chairperson Takshashila Institution, co-author of When the Chips Are Down) breaks the AI race into four competing narratives - nuclear standoff, arms race, innovation race, or diffusion game - and maps the five-layer supply chain that decides who actually gets to build.

Plus: why "self-reliance" is the wrong ambition, and what "self-strength" looks like instead.

A geopolitics playbook for builders, not diplomats.

Tune in and share with the builders, policy makers and AI adopters you know would benefit from the insights.

Your AI just denied someone's loan. Who's responsible?

Not in your policy doc - actually, functionally responsible.Beni Chugh (Dvara Research Foundation) opens Season 2 with a conversation about AI accountability that most boardrooms haven't had yet: the Air Canada chatbot that promised something the company wouldn't honor, the aviation-safety analogy for AI (and where it collapses), and why "human in the loop" is starting to mean rubber-stamping thousands of decisions an hour.

Grab a seat at the table nobody's saving for the customer.

In this episode of AI’s Happy Hour, our host & CMO, Sujit Janardanan, sits down with the winners of the AIBoomi Startup Weekend, Bengaluru—a 24-hour idea-to-MVP buildathon that brought together a new generation of AI builders turning curiosity, local insights, and ambitious ideas into real-world applications.

From investment banking professionals and startup founders to postgraduate students, these innovators share what it takes to build under pressure, validate ideas quickly, and create solutions that address real-world challenges rooted in cultural and local contexts.

We explore:

• The shift from AI hype to meaningful, outcome-driven use cases
• Building impactful AI solutions with limited resources
• What it takes to go from idea to MVP in just 24 hours
• Balancing rapid experimentation with long-term scalability
• The difference between an everyday builder mindset and a hackathon builder mindset
• How collaboration, curiosity, and execution come together to drive innovation

This episode is a must-listen for emerging founders, aspiring builders, and AI enthusiasts who want a firsthand look at how the next wave of AI innovation is being created.

Tune in now and follow AI’s Happy Hour for more real conversations shaping the AI future.