Who Will Bell The Consumer AI Cat?

In India, almost every AI conversation today is about sovereign models, semiconductor fabs, GPU clusters, compute capacity, and the race to build the infrastructure powering the country’s AI ambitions. But after obsessing over these for a while now, investors are shifting their attention towards a far more unpredictable opportunity — consumer AI. And the question they are asking is: who will bell the cat? 

Their excitement is not irrational. Globally, consumer AI is rapidly moving beyond standalone chatbots and becoming deeply embedded inside mainstream internet products. From Canva and Notion integrating generative AI into everyday workflows to AI-native platforms like Character.AI, Perplexity, Cursor and Manus reshaping how users search, create, code and consume content online, a new generation of internet products has begun to emerge around AI-first behaviour.

Amid the current scheme of things, investors believe India, with its nearly 950 Mn internet users, mobile-first consumption habits and growing comfort with AI interactions, may finally be ready for its own consumer AI moment.

Building consumer AI is intricate, especially in a market as fragmented and behaviourally diverse as India. It is this problem statement that makes us ponder: can Indian founders build products that move beyond novelty and become part of users’ everyday digital behaviour? Let’s talk about this and more in this edition of The AI Shift.

Why Now?

As Indians become more comfortable interacting with AI, the next biggest AI opportunity is waiting to mushroom from creating consumer AI products. And at the centre of this opportunity will be consumer internet companies operating in consumer-facing sectors.

According to Natasha Malpani, the founder of Boundless Ventures, an AI-native VC firm that invests across consumer AI, infrastructure, vertical AI and robotics, India is particularly well-positioned for AI-native consumer applications because of the agility with which users are becoming comfortable with using AI.

She said factors like India’s population density, growing consumer appetite and increasing exposure to AI are creating strong conditions for AI-native products to scale rapidly. Early signals are already emerging across consumer-centric sectors, including education, healthcare, commerce, among others. 

Rishabh Katiyar, partner at Info Edge Growth Fund, believes India’s breakout AI stories could also come from consumer AI companies capable of building social, habit-forming products.

“I would put my money on consumer AI because I see them growing very fast and becoming sizeable in just 3-5 years,” Katiyar said.

So, where can the monetisation opportunity emerge from?

Shubham Gupta, cofounder and partner at Together Fund — an early stage investor that has backed startups like Emergent Labs and Composio — says AI tutors, personalised healthcare assistants and AI-driven commerce recommendations could become significantly more viable as models become cheaper, more context-aware and capable of memory-driven interactions.

Building Consumer AI Is Convoluted

All the investor enthusiasm aside, there is a key concern for observers — consumer AI is one of the hardest categories to build in India. Unlike enterprise software, where workflows are structured and predictable, consumer AI products operate in messy environments shaped by human behaviour.

Vardhan D, principal at Stellaris Venture Partners, an early stage venture capital firm that has backed AI-focused startups like Goodscore, Arrowhead and Dashverse, describes consumer AI as an unconstrained system.

“In B2B, the problem is defined. In consumer, you’re dealing with the full spectrum of human intent, language and context,” he said.

India further complicates that challenge because of its linguistic diversity, dialect variations and wide spectrum of digital maturity across users. Besides, consumer AI products require both high-quality experiences and low-cost processing of AI, which are difficult to achieve simultaneously. 

The equation, however, has begun to shift. Token costs are falling, model quality is improving significantly, open-source alternatives are maturing and fine-tuning is becoming easier.

“We are finally getting close to the sweet spot, very high quality at a very low price, which is exactly what consumer AI needs,” Vardhan said.

While there is enough headroom to grow, consumer AI monetisation will only come from products solving very specific user problems in a unique way. To get there, founders will need to deeply understand local user behaviour, cultural nuances, and workflows to build products that users keep returning to.

To accelerate this shift, VCs are moving away from broad “AI-for-everything” ideas to backing startups solving highly contextual consumer problems with strong user retention.

Will India See A ChatGPT Moment?

India’s ChatGPT moment could emerge from highly vertical AI-native products that are deeply embedded in specific consumer behaviours. Founders are increasingly moving beyond simple AI wrappers and automation tools towards products that continuously learn from users and adapt over time.

Several startups are now building what investors describe as ‘intent layers’ — systems that understand user behaviour, preferences, routines, and context instead of simply generating responses on command. In many consumer-centric sectors, founders are shifting their focus from pure engagement metrics towards outcomes, trust, and long-term user retention.

For instance, an AI tutor that understands how a student learns over months, an AI healthcare assistant that tracks patient history and habits, or an AI shopping companion that remembers preferences and budgets could eventually become far more valuable than generic AI chat interfaces. Such products also build strong behavioural lock-in, as the accumulated user context becomes difficult to replicate elsewhere.

In essence, India’s real AI breakthrough will arrive when the most successful products stop feeling like “AI products” altogether. They may simply become seamless digital experiences embedded deeply into everyday life, much like how WhatsApp became India’s default communication layer without users ever thinking about the underlying technology powering it.

That is where India’s real consumer AI opportunity lies, not in building another chatbot, but in building products that become behavioural infrastructure for millions of users.

Top Stories From India & Around The World

• Paytm’s AI Push: The fintech giant is ramping up AI investments after achieving FY26 profitability. Paytm plans to deploy AI agents across merchant and consumer services. It plans to rent data centre infra and integrate AI into fraud detection, soundbox devices and product workflows.
• BigEndian Raises $6 Mn: The fabless semiconductor startup has raised fresh funding to commercialise its first surveillance-focused SoC. BigEndian plans to scale engineering, strengthen foundry partnerships and expand globally as India accelerates its semiconductor ambitions.
• Cloudflare Restructures For AI Era: The cloud infra company is laying off over 1,100 employees globally as it reorganises around AI-native workflows and agentic operations. Cloudflare said internal AI usage has surged 600% in three months, pushing the company towards leaner teams.
• Job Cuts At Freshworks: The SaaS company will lay off around 11% of its workforce amid ongoing operational restructuring. Despite reporting 16% revenue growth and narrowing losses in Q1 2026, Freshworks continues to optimise costs while adapting to AI-driven productivity shifts.
• Coinbase Trims Workforce: The crypto exchange is cutting nearly 14% of its workforce as it restructures around AI-native operations. CEO Brian Armstrong said AI is dramatically improving productivity, enabling smaller teams to execute work previously requiring larger organisations.
• Alphadroid Raises $3.8 Mn: The Delhi NCR-based robotics startup has secured funds in a pre-series A round led by Alkemi Growth Capital to scale its AI-powered automation systems. Founded in 2023, the startup offers robot-as-a-service solutions to enterprises.

The Weekly Buzz: Meesho’s AI Engine

AI is no longer just improving ecommerce operations, it is reshaping how India’s next wave of internet users shop online. In its latest shareholder letter, Meesho revealed how deeply AI is now embedded across its platform, from product discovery to logistics and customer support.

The company said over 70% of its code is now AI-generated, helping accelerate product releases and platform experiments. Its recommendation engine, PRISM, processes trillions of inferences daily and drives over 75% of orders through personalised feeds.

Meesho is also betting heavily on voice-led commerce through Vaani, its AI shopping agent designed for vernacular and first-time internet users. The company claims 1.5 Mn users tried Vaani within a month, with conversion rates improving by 22% among adopters.

Beyond shopping, AI is powering Meesho’s logistics and support stack. Its GeoIndia LLM converts landmark-based Indian addresses into precise coordinates, while Chorus, its AI support agent, resolved 19 Mn customer calls without human intervention in FY26.

The larger takeaway is that Indian ecommerce may increasingly evolve around AI-native interfaces rather than traditional search and app navigation. For Meesho, the race is no longer just about selling products online but about building AI systems that understand how India shops, speaks, and transacts.

Startup In The Spotlight: Trupeer.ai

As enterprise software stacks become increasingly complex, product adoption now depends heavily on scalable onboarding, content, training videos, walkthroughs and documentation. But producing professional tutorials and support assets remains time-consuming, fragmented, and expensive for most teams.

Founded in 2025 by Shivali Goyal and Pritish Gupta, Trupeer.ai is building an AI-first product content platform that transforms a single screen recording into both a polished product video and structured documentation. The startup combines screen capture, AI scripting, voice generation and knowledge management into a unified workflow for enterprise teams.

Its intelligent recorder captures user actions, clicks, audio, and screen context simultaneously, allowing the AI system to automatically generate scripts, voiceovers, zoom effects, subtitles, annotations and branded overlays without requiring manual editing. The same recording is also converted into formatted step-by-step guides with auto-detected screenshots, exportable in PDF, Word, or Markdown formats.

At the core of the platform is a script-based editing engine where teams modify videos by editing text instead of navigating traditional timeline editors. Both video and documentation outputs are generated in under a minute, significantly reducing production timelines for customer onboarding, support, and training workflows.

Beyond creation, Trupeer offers branded knowledge bases with AI-powered video search, alongside Share Pages, a client-facing distribution layer that bundles tutorials, guides, and assets into trackable links with engagement analytics.

Having raised a $3 Mn seed round last year, Trupeer claims over 35,000 teams as users, including Adobe, Glean, Zuora, Accenture, Diageo, and Zomato. As AI increasingly reshapes enterprise workflows, Trupeer is positioning itself as a content automation layer for software adoption, operating in an AI video generation market projected to grow from $716.8 Mn in 2025 to over $3.35 Bn by 2034.

Prompt Of The Week

What prompts and hacks are CTOs, CEOs and cofounders using these days to streamline their work? 

Here’s the prompt used by Anjan Pathak, the CTO and cofounder of Vantage Circle, to turn scattered updates into a personal leadership workflow assistant.

“Act as my personal workflow assistant. I am the CTO and co-founder of Vantage Circle, a B2B SaaS company building employee recognition and wellness products.

I oversee technology, marketing, product and people management, so my work often gets scattered across meetings, emails, and quick team conversations. I will provide the raw weekly updates along with the necessary context.

Organise the output by team or function. For each one, identify the priority, current progress, blocker, owner, and next action.

Then answer: 

• What needs my direct attention today?
• What decisions are waiting for me? 
• What can be delegated to team owners? 
• Where are updates repeated, unclear, or stuck? 
• What should be added to our Team Operating System so leadership can track it better?
  

End with a short morning briefing: top priorities, pending decisions, and follow-ups I should not miss.”

Editor’s Note: Some prompts may need to be adjusted by users for best results or may not work as intended for certain users.

[Edited by: Shishir Parasher]
[Creatives by: Abhyam Gusai]

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