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Joined December 2009
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Krishna Veera Vanamali retweeted
A pair of earbuds is a few grams of plastic, metal and electronics, made across several factories before it reaches a pocket. Solar panels, circuit boards and wind turbines are built the same way.
For years, buyers had to juggle those factories themselves, while the one with exactly the right machine often never heard about the order. ZETWERK (@zetwerk) set out to close that gap.
We first partnered with Amrit Acharya (@acharyaamrit) and Srinath Ramakkrushnan (@srinathramki) in 2019. Since then, that idea has grown into a network of nearly 7,000 suppliers, serving customers in 29 countries across energy, precision products and capital goods. Along the way, Zetwerk has brought work to builders from workshops in India to factory floors in Germany. Amrit and Srinath were joined by Vishal Chaudhary, Ankit Fatehpuria and Rahul Sharma in their journey.
Today, Zetwerk’s name goes up on the NSE and BSE. Behind that name are thousands of people who built it, one part at a time.
Congratulations Amrit, Srinath and the entire Zetwerk team. This film is for all of you, and everyone who builds with you.
@bsomaia
Krishna Veera Vanamali retweeted
An exciting day for the @zetwerk team.
Eight years ago, @acharyaamrit and @srinathramki set out to restructure global manufacturing around reliability.
Today, Zetwerk is going public with the same commitment to on-time and in-full delivery. When a customer’s order arrives in full on the date promised, the many years of waiting on suppliers shrinks and once scattered capacity becomes plannable.
From a young marketplace to a manufacturing ecosystem now serving customers in 29 countries. Congratulations on the listing Amrit, Srinath and team!
@LightspeedIndia @lightspeedvp
Krishna Veera Vanamali retweeted
🔊 The Investment Memo, Episode 1 🎙️
Every partnership at Lightspeed starts with an investment memo, where our team writes down what it believes about a company before we partner with it. In The Investment Memo, our new series, we open that memo with the founders it was written about and read from it, so you can see how an early investment decision is made.
Our first episode is with @SuperLivingApp, which is building an AI health coach for India, starting with users in tier 2 and tier 3 towns. People already ask AI about their health, but they rarely get someone who checks in with them the next day, and SuperLiving's coaches remember each user and follow up, at a price most families can pay.
We partnered with Manavdeep Singh Grover and Gurjot Kaur early at SuperLiving's Series A. When we wrote our memo, the app had 24,000 paid subscribers after about four months. Both founders came from Pocket FM, and they have shaped the product around what their users asked for.
In the episode, Lightspeed Partner @kumarharsha2212 and Vice President @PriyalMotw89880 read our memo to Manavdeep and Gurjot section by section, from the team and market to the risks we noted, and discuss what has shifted since.
Watch the full episode here: tinyurl.com/SuperLivingPodca…
day two - i am at the spot and it has been transformed beyond recognition!
we transformed the most dirtiest garbage dump in bangalore to a footpath with the great tiranga flag and HAL tejas on the walls, in less than 10 days.
a lot of you have asked to share what steps did we take to make this happen so @arunpaiblrwalks and i made a video about it.
this was a joint effort between @GBA_office and civilians.
Krishna Veera Vanamali retweeted
Most of India's consumer products were designed for its top 10%. The next 300 million are the users they have never reached.
They have long been viewed as a market with limited spending power. Lightspeed Partner Rahul Taneja (@rahultaneja) writes that this is likely the wrong diagnosis, and that they have been too expensive to serve. The cost of serving them is now falling fast. With AI, a founder can build a very different kind of team and infrastructure, and reach them at a fraction of the old cost.
His write-up, adapted from his recent consumer track session at the Google for Startups x Lightspeed Sprint, looks at what that change makes possible, assumptions most platforms still make about their users, and the principles for building products native to Bharat.
Read here: tinyurl.com/Building-for-Ind…
Krishna Veera Vanamali retweeted
One evening, many familiar faces, and a year’s worth of milestones to celebrate.
Here’s a look back at our Diwali Gala last week with founders, operators, and friends from across the ecosystem.
Thank you to everyone who joined us and made the night so memorable. Wishing you all a joyful festive season ahead! 🪔
@dkhare @kumarharsha2212 @rahultaneja @MohapatraHemant @romitme @BaggaRohil @ishaanpreet @JainAnuvrat @vivekgambhir @SeekingN0rth @sidsangwan @VinayakMishra09 @AmitMeh97501351 @PriyalMotw89880
Krishna Veera Vanamali retweeted
At @abhinavxarora and @itsmanvishah's Marketing Supper Club last week, where among friends and fellow marketers, I did my first book signing. :)
Also, @sai_ganesh and @whyvanamali having fun at my expense!
Krishna Veera Vanamali retweeted
We’ve updated our market map for AI assistants!
Ever since we published Lightspeed Partner Harsha Kumar's (@kumarharsha2212) observations on AI assistants, founders and readers have written in with names that should be added, several of them building in India. We have updated our market map to reflect the additions.
Harsha spent the past year meeting founders building AI assistants and wrote down what she saw. Her notes cover where the moats are and are not, which wedges work for India, and why the family, rather than the individual, may be the ideal customer.
Read it here: tinyurl.com/AiAssistantNotes
Krishna Veera Vanamali retweeted
The last month's been insane, the next year's going to be even crazier; some (rambling) thoughts on how our lives change
If you're trying to make sense of the circular deals in AI, I made a handy interactive website about them. The data comes from FT Alphaville citing Sona Asset Management. Click any company to see who has promised it money and who it has promised money to.
The money often moves in a loop. First, a chipmaker invests in an AI lab. Second, the lab uses the money to rent compute from a cloud company. Third, the cloud company buys the chips. Each company can be an investor, supplier and customer of the others.
The closest historical parallel is late-1990s US telecom, when telephone equipment makers did the same for phone companies. The phone companies laid fiber cables ahead of the traffic. The traffic arrived years later than the lenders had expected.
Such a supplier expects strong demand, because it risks its own money. The customer cannot yet pay from its own revenue. The spending pays off only if companies and people outside the loop (us basically) pay enough for AI. They need to pay before the chips get old.
The map is at - ai-money-map.vercel.app/
Krishna Veera Vanamali retweeted
Voice AI in Indian financial services is an outbound story, and the people building and running it say the human still closes.
Last week we hosted Off the Record with ElevenLabs (@ElevenLabs) in Mumbai, an invite-only evening on voice AI in banking, financial services and insurance, on the sidelines of the Global Fintech Fest (@GffFintechfest). 50+ tech, product and business leaders from across BFSI joined Karthik Rajaram (General Manager & Country Leader, ElevenLabs India), Santosh Bhat (Chief Data Scientist, Policybazaar.com), and Neel Gemavat (Lead - Generative AI, ICICI Prudential AMC Ltd), with Priyal Motwani from our team moderating.
The most valuable part of the evening was hearing our guests describe what is already running in production rather than what might. Key insights:
> Outbound before inbound: an outbound call is narrow and measurable, so AI already runs outbound campaigns at scale. The bot asks one question, whether the customer is interested, and hands every yes to a relationship manager.
> Cost is the wrong business case in India: contact-centre labour is cheap here, so replacing it does not pay the way it does in the US. The case is built on renewals, persistency, CSAT and conversions instead.
> Tier 2 and 3 trust the bot, metros spot it: outside the metros, a structured voice gets the query resolved instead of a branch visit, while metro customers recognise the AI and want a human for the emotional edge cases.
The Q&A showed how close the room was to deployment. Questions ran from whether voice can fix mis-selling in Tier 2 and 3 by explaining a policy before purchase, to whether the interface moves to WhatsApp, to what the disclosure rules will require.
Thank you to Karthik, Santosh and Neel for their candour, and to the ElevenLabs team for putting the evening together with us.
Detailed takeaways from the session are coming to our Substack. Subscribe here: tinyurl.com/lsipsubstacksub
@policybazaar @ICICIPruMF @PriyalMotw89880 @JainAnuvrat @TejasJ1210 @basbhaimomo @ishaanpreet @rutabhatt @SeekingN0rth @nityabaskar @whyvanamali
The personal AI agent wars are on! We are firmly in the third wave of modern AI, going from foundation models that can think/talk (ChatGPT era) to autonomous execution on complex tasks (Claude Code era) to persistent, personal-state agents with an aggressive bias for finishing real-world tasks (Instinct, Poke and Muse from Meta launched 8 hours ago).
Yes the market map is already outdated!
Consumer agentic AI / “personal operator” category finally feels real and inevitable. Combining computer-use capabilities + simple messaging UX + deep personal context can create genuine delight and time savings for everyday tasks.
At Lightspeed India, we have been tracking this space for over a year, and in this piece, Harsha Kumar has penned her observations from meeting founders building AI assistants.
Some thoughts and ideas:
> While automation is generally seen as the goal for all products, human-assisted AI will persist exclusively for an "ultra-premium" category seeking exclusive, non-mass-market services
> Although the market currently separates personal and professional AI agents, this distinction won’t last long. Well-designed agents will eventually abstract away different data silos (e.g., personal vs. financial/work data)
> Data is unlikely to provide a moat because your competitor can easily pull the same data from email, messages and all other connected tools. The real moat will be brand, habit, and derived context (what you learn about the user over time)
> In India, call screening is an unusually useful insertion point. Successfully solving call screening earns the assistant the trust and data needed to move into more complex tasks like making calls on the user's behalf, discovering offline vendors, and delegating tasks to household staff
> "Family as a unit" is actually a better TG target than focusing just on individuals. This solves the frequency problem—households generate daily tasks without conscious effort—and offers a data set (family context) that isn’t currently aggregated on digital platforms.
I for one strongly believe a personal AI agent product could become the next Facebook. Agents deployed directly into existing/creating new social graphs create network effects. Once an agent maps your personal life, integrates with your communication channels, and establishes inter-agent channels across your family and social circle, dropping out means losing that shared context and effortless coordination, creating an unbreakable lock-in.
Read: tinyurl.com/LightspeedAiAssi…
