We’re opening up @GnaniAi to student builders. The Great Indian AI Internship Challenge is now live. The idea is simple: Build something useful with Gnani AI’s models and APIs, show us how it works, and put your work in front of the team here. There are up to 100 paid internships available, with individual stipends of up to ₹1 lakh per month for selected interns. You’ll also get: 1. 5,000 programme credits to build with. 2. Access to Prisma, Timbre and Evon. 3. 10 award categories across language, creativity, real-world impact, demos and more. 4. A chance to be shortlisted for an internship with Gnani AI. You can build solo or with one teammate. What you need to do: Step 1: Register at gnani.ai/great-indian-ai-int…. Step 2: Pick a unique problem. Step 3: Build using Gnani AI models or APIs. Step 4: Record a working demo. Step 5: Post it on LinkedIn or X. Step 6: Submit before November 10, 2026. That’s it. No fixed idea list. No single “right” project. We want to see what you choose to build when the tools are in your hands. Submissions close November 10, 2026. Start Building!! #GnaniAI #GreatIndianAIInternshipChallenge #AIInternship #StudentDevelopers #BuildInPublic #DevelopersIndia

Launch Series : Day 10/10 Introducing scenario-based prompting in Gnani AI's Agent Builder. The agent gets the instructions for the step it is on, so token usage and latency stay low as the conversation grows. Link in the comments. #VoiceAI #AIAgents #AgentBuilder

Launch Series : Day 9/10 A phone call usually gives you words. Nothing to look at, nothing to scroll back to, nothing to tap on. But some moments need more than talking, a menu to pick from, a confirmation to glance at, a step that’s easier shown than said. Our AI voice agent on WhatsApp handles exactly that: it carries the call like any other, and the instant something’s easier to show than say, it lands straight in the same chat, no separate app, no “check your email.” The call and the chat aren’t two channels. They’re one conversation, working the way a conversation should. #VoiceAI #ConversationalAI #WhatsAppBusiness #CustomerExperience #Gnani #AIAgents

Launch Series : Day 8/10 Introducing Gnani AI Agent API. Build and manage voice agents from your own platform, connect existing workflows, and bring conversation data back into your systems. Explore more in our blog. #GnaniAI #VoiceAI #AIAgents #EnterpriseAI

Launch Series : Day 7/10 Introducing Agentic Evals by Gnani AI, built to make sure every agent is ready before a real customer calls. Agentic Evals runs simulated conversations and edge cases designed to break the agent, and scores each one out of 100. Below 80, an agent doesn't go live. Teams cut QA time by roughly 90%, with a record of everything checked before launch. Learn more in our detailed blog. Link in the comments #VoiceAI #AgenticEvals #EnterpriseAI #AIAgents #AITesting

Launch Series : Day 6/10 Introducing AI Insights, built to help enterprises understand their customers and the context behind what they ask. #VoiceAI #AIInsights #EnterpriseAI #CustomerExperience

Launch Series : Day 4/10 What does it take to build a language model that serves India in its own languages? 1.27 trillion tokens of continued pretraining. A vocabulary extended with 32,000 Indian-script tokens. And research into what happens when benchmark scores improve while answers drift into English. Our new white paper documents the research and engineering behind Gnani Evon v3.3, the experiments, fixes and trade-offs across the full training pipeline. Read the full white paper: gnani.ai/resources/research/… hashtag#GnaniAI hashtag#SovereignAI hashtag#LLMResearch

Launch Series : Day 3/10 Every laugh and pause in this video was generated by our AI model. This is Timbre 3, our new text-to-speech model, live today on the Gnani API. Timbre 3 introduces expressions in your speech in the form of audio tags. You write a short cue where the delivery should change, and the voice performs it. There are 12 of them, covering laughter, breath, vocal style and pacing, across 11 Indian languages and many voices. We built it for the places voice already does real work: → Voice agents and IVR that soften when they apologize and slow down when they read out an amount → The voice layer inside apps, from learning lessons to game characters → Creator productions, where the acting now lives in the script Under the tags, Timbre 3 reads numbers and dates the way people say them, with natural prosody across every voice. What would you make it say first? #VoiceAI #TextToSpeech #Timbre #TTS

[Launch Series : Day 2/10] Most KYC checks sit in a queue before anyone even looks at them. On Plexus, an agent reads the PAN card the moment it comes in, pulls out the details, and calls the customer to confirm them directly, no manual entry, no back-and-forth over email. The verification that used to sit in a queue now happens in one continuous flow: document in, call placed, confirmation done. Automate every workflow with Plexus. Join the waitlist: gnani.ai/plexus-early-access hashtag#AgenticAI hashtag#VoiceAI hashtag#ConversationalAI hashtag#Automation hashtag#Gnani hashtag#AIAgents hashtag#KYC

Launch Series : Day 2/10 Introducing Gnani’s multichannel agentic platform. Build AI agents, give each one a clear job, and connect them into workflows that carry a task from start to finish. Guardrails sit underneath all of it, so every agent knows exactly where its job ends and when to bring a person in. And with 150+ integrations built in, these agents plug straight into the systems you already run on. Join link gnani.ai/plexus-early-access #AgenticAI #VoiceAI #ConversationalAI #Automation #Gnani #AIAgents

Launch Series : Day 1/10 For the next 10 days, Gnani is shipping something new every day. We’re starting with the biggest one: EVON v3.3, our own LLM. For many people in India, the first language they reach for is Hindi, Tamil, Odia or Punjabi. The AI behind the products they use should meet them there. That’s what we built Evon 3.3 for. Evon 3.3 is Gnani’s own LLM. It reasons and acts in English and 10 Indian languages, so developers can build products that reach people in the language they speak. From 12 October, we’re opening early access on the Gnani API to 1,000 developers. What you’ll build with: → Tool calling for agents that get things done → 128K tokens of context, enough for a full document in one request → Thinking mode for the harder problems → English, Hindi, Bengali, Telugu, Tamil, Marathi, Gujarati, Kannada, Malayalam, Odia and Punjabi, in one model Join the wait list: gnani.ai/evon-waitlist Follow this space for the rest. #Evon #GnaniAI #IndianLanguages #LLM

AI doesn’t scale alone. Getting AI from pilot to production takes more than a good model. It takes the right technology, infrastructure, implementation expertise and partners working together. That’s why we built Gnani Ascent, our flagship partner program. Gnani Ascent brings together technology partners, system integrators, cloud and infrastructure providers, consulting firms, CCaaS/CPaaS platforms, OEMs, silicon partners and go-to-market teams to build and scale production-ready AI solutions with Gnani. Partners can work with us across joint solutioning, implementation, integrations, embedded AI and go-to-market, using the Gnani stack across Evon, Timbre, Prisma, Warp and Plexus. And this isn’t an ecosystem we’re hoping to build someday. More than 25 partners are already part of the journey, including Hexaware, Intel, Cisco, Fortanix, Vymo, Rise and iSteer. The idea behind Gnani Ascent is simple: Build together, Go to market together, Scale AI together because frontier AI may start with intelligence, but it scales through an ecosystem. Explore Gnani Ascent: gnani.ai/partner-program

Your AI agents call thousands of people every day. Most teams see two numbers from that: calls made and calls connected. The real story sits in between. Where the conversation dropped. Which hours nobody picks up. Which language converts. Why "interested" never became "booked." That's what Gnani Insights is built to show you. → The full calling funnel in one view: dialed, connected, engaged, positive disposition → An AI summary that points to where the drop-off is happening and what to change → Every call logged, with the recording and transcript side by side → Hour-by-hour connectivity, so you know when to dial and when to hold off → Compare any two metrics by language, time of day, or any field in your data → Secondary metrics too: agent transfers, completion rate, average attempts See what's working. Improve what's not. Know every call like you were on it. Watch the walkthrough below. #AIAgents #ConversationalAI #CustomerExperience #Analytics #GnaniAI