gnani.ai

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Mumbai!!! That was incredible. We brought together the sharpest minds across the board: our customers, prospects, partners, and investors for a massive day of conversations in Mumbai.   The energy in the room made one thing undeniably clear: the conversation around Voice AI has completely shifted. This isn’t just about the next frontier for India anymore. It’s about how Voice AI is fundamentally restructuring our systems, defining how enterprises operate, across every single industry.   We didn't just talk about the tech; we talked about how we are actively shaping it.   A massive thank you to everyone who showed up, challenged ideas, and shared their feedback. The momentum from yesterday is going straight back into the product.   We’re just getting started!   #VoiceAI #EnterpriseTech #Innovation #MumbaiEvent #GenerativeAI

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The stage is heating up. We’ve moved from the high-level strategy to the "in the trenches" reality check. We’ve got our CRO, Vasuta Agarwal moderating a powerhouse panel with Manish Kumar Gupta from L&T Finance, Vimal Saboo from Fibe.India (Formerly EarlySalary), Akhil Duggal from Crompton Greaves Consumer Electricals Limited, and Ankit Goenka from Bajaj General Insurance. They aren't talking about "if" Voice AI works anymore; they're dissecting the actual business impact of from the early adopter point-of-view. The pabel is focused on the hard metrics: 1. How does this actually move the needle on growth? 2. What happens when you move from the initial "aha!" moment to high-volume, daily operations? 3. Where is the ROI hiding in the real-world deployment? It’s refreshing to hear leaders pull back the curtain on their own implementation learnings, the good, the bad, and the unexpected. We’re finally getting the answer to the only question that matters: Does this actually survive the chaos of real-world use cases? #FutureOfVoiceAI #GnaniAI #EnterpriseAI #VoiceAI

Sitting in on "The Future of Voice AI" here in Mumbai. We’ve got a brilliant panel breaking down the levers that move AI decisions at enterprise scale. Naveen Mishra from Gartner is digging into the adoption curves we're seeing across the industry, while Aditya (adi) Jayaraman from Hexaware Technologies is tackling the engineering reality of building for the unique, code-switching complexity of the Indian market. The conversation is a needed pivot from the usual "AI’s endless potential" fluff. We’re focused on the tension between: The Production Gap: Why so many enterprise pilots fail to translate into day-to-day operations. Structural Advantage: Whether our linguistic diversity is a hurdle or an edge for building resilient, production-grade models. The Guardrail Paradox: How to bake in security without strangling the performance of mission-critical systems. #FutureOfVoiceAI #GnaniAI #EnterpriseAI #VoiceAI #BFSI

Ganesh Gopalan, CEO and Cofounder of Gnani kicks things off at our Mumbai event with a sharp set of insights. The builders of tomorrow here aren't talking about "next-gen models" when looking at conversional AI innovation, they’re talking about the brutal economics of production-scale voice AI. The takeaway from the floor today: You can’t import your way to success with a Silicon Valley playbook. Building for India means dealing with patchy infra, at least 20+ languages, and unit economics that don’t follow the SaaS-bubble math. Gnani.ai’s focus on sovereignty isn’t a political stance. It’s an engineering necessity. If your AI doesn't handle real-world latency at millions of calls a day, it’s not an agent; it’s a demo.  We’re past the era of the "wow" factor. We’re in the era of the "does it survive production?" factor. Ananth Nagaraj Bharath Shankar Vasuta Agarwal Rajesh Rajyalakshmi Pantina Om Joshi Arunabh Biyani #AIInIndia #BuildInPublic #VoiceAI #RealWorldAI #Inc42Summit

LIVE NOW: The Future of Voice AI, Mumbai Edition   Sound checks are over. We've officially kick-started the Mumbai leg of our event and the room is packed.  For those following insights around conversational AI, here's what will be up for discussion today across multiple sessions spanning a panel discussion and a fireside chat. We will explore: 1. Multilingual Voice AI and its critical role in BFSI 2. Solving for a tightly regulated environment 3. The gap between pilots and production deployment   This is the conversation happening in real-time. If you're building or solving for this space, you're in the right room.   Stay tuned to this space for more updates.   #VoiceAI #BFSI #TheFutureofVoiceAI #GnaniAI  

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Everyone's testing in a soundproof booth. Your customers are yelling over a fan. Most voice AI benchmarks? Studio conditions. Perfect isolation. Clean audio. Pristine. Which is great if your customers call from NASA. In Indian call centers, the acoustic signal is chaos. 8kHz sampling rate that chops high frequencies. GSM codec compression that artifacts everything. Background noise : AC units, traffic, twenty other conversations bleeding through. And mid-sentence, your caller switches from English to Kannada to Telugu because that's how Indians actually speak. Standard benchmarks measure WER in that perfect booth. Looks great on a slide. Then you deploy to production and watch your model fail on the exact conditions it will face 10 million times a day.   We didn't test in a booth. We tested on what's actually happening.   Gnani's proprietary STT model is trained across 22 Indian languages on real 8kHz noisy telephony data. On actual Indian call center audio (not studio conditions) it outperforms ElevenLabs, Sarvam, and other competitors across the board.   The margins look modest on paper. Until you scale it. At 10 million interactions per day, each 1% difference in accuracy is 100K+ extra misunderstood calls daily. Broken workflows. Lost revenue. Customers hanging up.   Building for Indian telephony isn't a feature we added. It's the only baseline that matters.   #IndiaAIMission #GnaniAI #AIforBharat

Most voice AI benchmarks test on studio-quality audio. Then they ship to the real world and everything breaks.   Here's what actually happens in Indian telephony: 8kHz sampling, GSM compression eating the signal, five people talking in the background, and your caller just switched from Hindi to English mid-sentence. The model trained on clean recordings has never seen this.   It fails. Silently.   This is the gap we are trying to bridge at Gnani. It is not an edge case, it's the baseline.   We benchmark on Kathbath Noisy, which is actual telephony data, actual noise. Gnani’s proprietary ASR hits 17.5% WER. ElevenLabs: 19.1%. Sarvam 3.0: 19.9%. Two percentage points doesn't sound like much. But at 30 million calls a day, those percentage points are broken workflows, misunderstood intent, angry customers.   They compound.   Building for Indian conditions isn't a feature you bolt on later. It's what you build first, or your product won't work here at all.   #IndiaAIMission #GnaniAI #VoiceofBharat