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Episode 180 · Capital · 48 min

Invest where India needs to invest

Shashank Randev and Yagnesh Sanghrajka left 100X.VC to start 247VC, a ₹250 crore seed fund. They back deep tech at the prototype stage and value it on technology milestones, since there are no cash flows to discount.

Venture capitalDeep tech & hardwareAI & machine learning
SR
YS
Shashank Randev and Yagnesh Sanghrajka
Co-founders, 247VC · with Vishal Krishna and Shreyas Mishra
Invest where India needs to invest: episode thumbnail
48:20
The brief

The argument in sixty seconds

247VC will “invest where India needs to invest”, Yagnesh Sanghrajka says: in quantum, space, semiconductors and photonics, because in his view consumption has “played out pretty much”. Shashank Randev screens founders on five points, and Yagnesh adds a sixth, coachability, because scientists often miss what follows TRL 6 or 7. Shashank’s case in point is a battery company the pair backed at TRL 3, when it had only a prototype. Four and a half years on, it sells to vehicle makers. In enterprise AI they want services firms that build a proprietary system of record; without one, Yagnesh says, a rival can copy the work.

Disclosure: EMO Energy and Stupa Sports Analytics, both discussed on air, are earlier investments of the partners (EMO through 100X.VC in 2022). Dream Aerospace, also discussed, is 247VC’s first investment.

The thesis, drawn

Eleven charts, forty-eight minutes

Figures are as said on air unless marked. Fund terms come from launch coverage (Inc42, May 2025); EMO Energy’s rounds from EVreporter and Venture Intelligence; the Panasonic cohort from Panasonic. Click ▶ to hear them.

Thirty seed bets in three years

247VC India Fund I · as said on air, with launch coverage (May 2025)
Money and track record
India Fund I, ₹ crore200 base+50 greenshoehow it is splitfirst cheques 50–55%follow-onsthe partners’ pre-seed record200+ companies50+ in deep tech or manufacturing
Thirty bets
30 investments planned2 made so far; Dream Aerospace firstfirst cheques of ₹3–4 crorefund life, years from 20259 years+2, as Vishal puts it
247VC is a SEBI Category II fund, launched in May 2025. Shashank says about half is raised; the life of nine years plus two is Vishal’s figure. It co-led Dream Aerospace’s ₹10 crore round, for green satellite propellants, in June 2026.▶ 0:21▶ 0:43▶ 1:24▶ 4:34

Where the 30 cheques are meant to go

the four themes and the sub-theses named on air
Deep tech
Quantum, space, chips
SNSPDs and cryogenics, green propellants, quantum photonics, AI drug discovery
Manufacturing
Factories that measure
IoT that sells its data, digital twins, energy management
Enterprise tech
AI-native services
an “AI services era” after IT services, built for enterprises in India
Consumer tech
The first wave
where the last decade’s winners came from; little discussed on air
Yagnesh ties the first two themes to government missions and the India 2047 vision. Sports analytics came up too, but a sector needs about a dozen startups to yield two or three outliers, he says, so it may wait for a second fund.▶ 0:58▶ 4:51▶ 26:18

Stickiness comes from owning the system of record

how an AI-native services firm gets sticky, as Yagnesh describes it
System of recordunique to you, maybe for 5 yearsProprietary workflowsbuilt once, reused at other clientsOrchestration layeragents in the client’s systemsFoundation modelseveryone builds on the same onesstickieragents take on the volume work;people stay on for QC and QA
Good AI-native services startups are still rare, Yagnesh says. Enterprises guard their data, so the startup’s people work inside the client first and deploy agents from there. Agents could replace people outright only if clients allowed it, and he doesn’t think India is there yet.▶ 26:57▶ 28:26▶ 30:54

Five checks, then coachability

how they screen an early deep-tech startup, in Shashank’s order, plus Yagnesh’s sixth
1
Team
founder–market fit; a business person beside the professor
▶ 7:31
2
Opportunity
the fund’s own research on market size
▶ 7:52
3
Business model
“technologies which become businesses”
▶ 8:02
4
Moat
and whether it lasts two, three or four years, given AI
▶ 8:13
5
Value added
what the fund brings after the cheque, through its advisers
▶ 8:28
+1
Coachability
“it’s like a marriage”
▶ 8:45
Scientist-founders often lack business, monetization and go-to-market skills, Yagnesh says, so they must listen to investors. Even a Stanford and IIT battery founder needed help with management reports and balance sheets, Shashank recalls. The firm’s core team is half engineering or pharma, half finance.▶ 45:29

Enter at TRL 3, then help it climb

NASA’s nine technology readiness levels · their markers, as said on air
123456789they enter atTRL 3–4and help it climbto TRL 7–86–7: “clueless”TRL 1: basic researchTRL 9: in usestartups that end up using the tech elsewhere6 in 10
Six in ten startups end up using their technology somewhere other than planned, Yagnesh says, often once they reach TRL 8 or 9 and the market turns up elsewhere. Even at TRL 9, Shashank adds, a technology can lose its adaptability.▶ 5:53▶ 9:41▶ 22:11

TRL 3 to 25,000 packs in 53 months

EMO Energy, which the partners backed at TRL 3 · funding and deployment records
May 2023 · $1.2M seed13 moJan 2025 · $6.2M Series A; 2,000+ packs33 moJun 2026 · ₹59 crore, valued ~₹860 crore50 moSep 2026 · 25,000 packs deployed53 mo01 yr2 yrs3 yrs4 yrsmonths after the TRL 3 cheque, Apr 2022
EMO makes immersion-cooled battery packs for two- and three-wheelers. Shashank calls it a homegrown product sold in India, with a “three-digit” valuation and “two-digit” yearly revenue; EMO reported about ₹14 crore of operating income in FY25.▶ 6:04▶ 10:21▶ 18:57

After TRL 6, four ways to cash in

routes to market, as Yagnesh lays them out
What the startup does
When it fits
Build and sell
▶ 23:57
Makes and sells its own product
It can manufacture at scale
Out-license
▶ 23:34
Innovates to a point, then a bigger firm takes over
“you don’t think you can build it, which is fine”
Transfer the technology
▶ 23:40
Moves across with the buyer until it works in the field
The buyer needs the know-how too
Sell the IP
▶ 24:08
Sells the asset outright
Pharma, where a molecule can fetch “billions”
Early meetings are about the product, Yagnesh says; only as conviction grows does the talk turn to years five and six. Licensing abroad works from an Indian base too: “Nothing is not structureable.”▶ 9:41▶ 23:05

One problem, 140 applicants, two top awards

Panasonic Ignition, first cohort, run with 100X.VC in 2023–24 · on air: “almost 100 plus” applied
applied140+picked for the cohort12won an award6top award, Ignite2: Enlite, Claircothe problem: cut energy use in commercialbuildings as occupancy changes
A big building leaks energy on every floor, Yagnesh says, and its consumption should follow how many people are in each room. The partners only acted as a catalyst, he says; Shashank adds that Panasonic wanted the technology for its own facilities.▶ 15:58▶ 16:13▶ 17:17

Government goes first, family money follows

who funds deep-tech funds, as Yagnesh sees it · family offices in India, PwC count
Governmentfirst risk; RDI scheme of ₹1 lakh croreDeep-tech funds247VC and its peersPrivate LPs and family officesfollow once the value showsfamily offices in India (PwC)2018452024300+
The state’s appetite for risk is “way higher”, Yagnesh says, so private money waits for proof. Shashank finds third- and fourth-generation heirs curious about deep tech; older family businesses always invest in their own companies, Yagnesh adds.▶ 41:04▶ 41:28▶ 42:27

No predictable cash flow, no DCF

how to value a startup, as Yagnesh, a chartered accountant, puts it
Discounted cash flow
Technology milestones
Needs
▶ 43:45
Predictable cash flows and about two years of revenue
A clear view of the TRL and the founder
Diligence asks
Revenue, customers, cash generation
Which TRL the company has reached
Fits
▶ 44:15
Enterprise businesses with customers
Deep tech, where TRL 8 may be four years away
Founders and accountants who invent future revenue to run a DCF are using “a flawed concept”, Yagnesh says. Vishal suggests the chartered accountants’ institute teach milestone valuation.▶ 43:45▶ 44:15▶ 44:36

Nifty trades 20% below its ten-year average

Nifty 50 price-to-earnings ratio · Tapetide tracker of NSE data; consolidated earnings since 2021, standalone before
10-year average24.7×end of 202522.8×5-year average21.8×3 November 202619.7×010×20×25×price to earnings, Nifty 50
Yagnesh disagrees that India is expensive: multiples follow liquidity in the short run, fundamentals over longer spans. He expects deep-tech startups to list within five to ten years, and tech companies to weigh more in the Nifty by 2030.▶ 36:29▶ 36:45▶ 37:20
Worth keeping

Lines that stay

What India today needs is hardcore efficiencies on manufacturing.

Yagnesh Sanghrajka, on the fund’s thesis ▶ 2:04

We are as good as the people we work with.

Shashank Randev, on the fund’s specialist advisers ▶ 20:08
Chapters

Where the conversation travels

Every block is a chapter, coloured by what it's about. Click any of it to jump straight to that minute on YouTube.

0:00–0:37 · Introduction020:37–4:14 · The fund’s four investment themes034:14–7:11 · Space, quantum and the deep-tech investment thesis047:11–10:00 · How investors assess early deep-tech startups0510:00–11:44 · Domestic demand and import substitution0611:44–14:36 · IoT, digital twins and industrial efficiency0714:36–19:50 · Energy management and corporate partnerships0819:50–22:35 · Technology readiness, adaptability and advisors0922:35–26:03 · Commercialization, licensing and exits1026:03–27:55 · AI-native services and proprietary workflows1127:55–30:58 · Customer stickiness, data and systems of record1230:58–34:09 · AI agents as users and autonomous operators1334:09–37:37 · India’s technology opportunity and valuations1437:37–40:53 · Sports technology and emerging markets1540:53–43:30 · Indian family offices and deep-tech funds1643:30–44:53 · Valuing deep tech beyond DCF1744:53–48:20 · How VCs develop founders’ capabilities10:0020:0030:0040:0048:20
Venture capitalDeep tech & hardwareAI & machine learningManufacturingIndia macroFounder journey
01Introduction 0:00 02The fund’s four investment themes 0:37 03Space, quantum and the deep-tech investment thesis 4:14 04How investors assess early deep-tech startups 7:11 05Domestic demand and import substitution 10:00 06IoT, digital twins and industrial efficiency 11:44 07Energy management and corporate partnerships 14:36 08Technology readiness, adaptability and advisors 19:50 09Commercialization, licensing and exits 22:35 10AI-native services and proprietary workflows 26:03 11Customer stickiness, data and systems of record 27:55 12AI agents as users and autonomous operators 30:58 13India’s technology opportunity and valuations 34:09 14Sports technology and emerging markets 37:37 15Indian family offices and deep-tech funds 40:53 16Valuing deep tech beyond DCF 43:30 17How VCs develop founders’ capabilities 44:53
Glossary

The jargon, unpacked

Technology readiness level (TRL)
A nine-level scale devised at NASA. TRL 3 is an experimental proof of concept, TRL 6 a prototype tested in a relevant setting, TRL 9 a system proven in use.
Greenshoe
An option to accept commitments above a fund’s target.
SNSPD
Superconducting nanowire single-photon detector: a wire cooled close to absolute zero that registers single photons, used in quantum communication and computing.
Transfer of technology
Handing a buyer the know-how as well as the rights, with the inventors helping it work in production. Out-licensing grants the rights alone.
System of record
The authoritative store of a business’s core data, such as customers, orders or assets, which other software reads from and writes to.
Discounted cash flow (DCF)
Valuing a business by forecasting its future cash flows and discounting them to today’s money. It needs predictable revenue to work.
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Full transcript

The whole conversation, searchable

350 segments
SRShashank Randev, 247VCYSYagnesh Sanghrajka, 247VCVKVishal Krishna, UpStreamVoiceSMShreyas Mishra, UpStreamVoice

Machine transcript of the recording, attributed to speakers from the diarization and context, and lightly edited: fillers and brief interjections such as “Mm-hmm” are left out; [unclear] marks words that could not be recovered. Speaker labels in the sports and founder-discipline passages are least certain. Click a timestamp to open that moment on YouTube.

Checked against the record: EMO Energy, the battery company Yagnesh names at 18:57, raised its $6.2 million Series A, led by Subhkam Ventures, in January 2025; its latest round was a ₹59 crore pre-Series B led by Raghav Capital in June 2026 (said: “just last month, they were able to raise their Series A”). We found no report of a merger between startups from Panasonic Ignition’s first cohort; its two winners, Enlite and Clairco, are reported separately, and Enlite raised a ₹46 crore Series A on its own in 2025 (said: “two of the top awarded startups actually merged”). The widely reported figure of 300 counts family offices in India, up from 45 in 2018 (PwC); we found no count of Indian family offices that have moved to Singapore (said: “300 family offices have moved to Singapore”). At the IIT Madras press Q&A in EP 177, the trillion-dollar figure came from a questioner, who put US and Chinese startup funding over ten years at about $4 trillion; Prof. Kamakoti’s “1 by 10” referred to his Shakti chip, built for ₹4 crore against about ₹40 crore in the West (said: “$2 trillion in the last 10 years”, “one-tenth the cost”). Sequoia’s March 2026 essay is titled “Services: The New Software” and does not declare software dead (said: “software is dead”). Information technology was 8.48% of the Nifty 50 in its August 2026 factsheet, against 36.47% for financial services (said: “it’s already heavily benchmarked with IT services”).