A woman having her hair styled in a contemporary Bangalore salon

Where India
discovers beauty

Ask what to buy. Find where to go. Discover who to trust.

Community · local discovery · commerce — built for beauty. Starting in Bangalore.
The product

This is Glow.

A woman in Bangalore opens Glow to answer the questions she'd otherwise put in a WhatsApp group. She asks her neighbourhood, she takes a side, and she lands on a place with the community's verdict already attached to it.

Glow home feed at 390px: a Hot/New toggle, category chips, an Ask Whitefield bar, and community questions including 'Which clinic for laser hair removal in Brookfield?'
Ask the neighbourhood
A Glow poll: 'Keratin treatment: worth the cost?' with three options and a Cast My Vote button
Take a side
A Glow business page for You Spark Family Salon showing rating, call and directions actions, service categories, and the Glow polls and discussions the salon appears in
Find the place — and what Glow says about it

Live screens from the Glow application, captured at 390px. Not mockups.

Why it compounds

Every interaction makes
Glow smarter.

R
Community member
Finally got my hair done at Bounce Whitefield 🙌
Glow
Who did your hair? 👀
R
Community member
Neha! Ash balayage, ₹4,500. Going back to her.

One ordinary exchange. Three details — Neha, balayage, ₹4,500 — and Glow now holds something neither Google Maps nor Instagram does.

That's the Beauty Graph.

People, places, services, the individuals who perform them, prices, and whether it was worth it — connected, searchable, and getting denser with every question asked.

Why it matters

Everyone knows a piece.
Nobody knows the decision.

Google Mapsknows where
Instagramknows what looks good
Ecommerceknows what people bought
Glow can know what people ask, what they consider, who they trust, where they go, and what they choose

That's the difference between a listing and a decision — and decisions are what local businesses and beauty brands actually pay to reach.

What's already built

One area.
Already mapped.

Marketplaces usually die building supply. Glow's supply engine already runs — it discovered, classified and scored every beauty business in Whitefield, with no data-entry team.

821
Directory-ready beauty businesses in Whitefield, in Glow's own data model
Verified
₹3,622
Marginal cost to map the next area — about $38
Verified
Live
Working product on a live backend, with the community layer ready to open
Verified

That graph is already in the product

Explore isn't a placeholder. It browses the real Whitefield directory — every category carrying its own counted supply, straight from the graph the pipeline built.

The moment a consumer opens Glow in Whitefield, there is something real underneath them. That is the half of a marketplace that usually takes a year and a team.

Glow Explore browsing Whitefield: 821 places, with category tiles for Salons and Hair (483), Nails (279), Skincare and Facials (470), Makeup (224), Bridal Beauty (223) and Brows and Lashes (224)

The supply engine is built.
Now we prove demand.

A colourist applying balayage to long dark hair
Hair
A manicure in progress in a nail studio
Nails
Eyebrow shaping in a brow studio
Brows & lashes
Geography

Bangalore is the laboratory.
India is the market.

Start dense in one neighbourhood. Prove the loop. Then repeat it — area by area, then city by city.

Built Next Modelled expansion
Business model

Consumers use Glow free.
Intent is what gets sold.

01
Local businesses
Pay for visibility and measurable intent — profile views, call taps, directions, saves. A salon isn't buying impressions; it's buying the woman two kilometres away who just asked who does good balayage.
Modelled first revenue
02
Area & category sponsorship
A business or brand owns the beauty conversation in a neighbourhood, or in a category.
Modelled
03
Beauty brands
Reach an endemic, urban, high-intent audience at the moment of consideration rather than after it.
Modelled at scale
04
Commerce
Every This/That vote is a preference signal that arrives before the purchase. Affiliate, CPC, CPA, sponsored comparison.
Upside layer
05
Intelligence
Once the graph is dense, aggregated demand signal becomes a product of its own: what India is asking for, by category, city and price band.
Long-term optionality

The economic architecture

Each layer exists because of the one before it. Community creates knowledge; knowledge makes discovery work; discovery produces intent; intent is what advertising and commerce are built on; and at sufficient density, the accumulated signal becomes intelligence.

At scale

What if Glow becomes where
India decides beauty?

Move the audience and the economics follow, using the same structural ratio the Whitefield build produced: roughly eleven addressable beauty businesses for every thousand active users.

Modelled scale scenario — not a forecast

Annual revenue mix at this scale

Local advertising Area sponsorship Brand advertising Commerce
Businesses advertising5%
1%10%
Advertiser pays / month₹2,499
₹1,499₹5,000
Brand inventory sold20%
10%30%

Off by default — commerce is upside, not the core case.

What ignition looks like in the operating model

The 36-month operating model, run on its upside case: contribution compounds, organic discovery opens up, and areas fill fast enough to monetise.

Modelled scale scenario · not current traction

What's next

Three questions
between here and scale.

The supply engine is built, so the next work isn't building — it's proving demand. Three questions, answered in ninety days, in one neighbourhood.

01
Will people use it?
Do Bangalore beauty consumers come back, contribute answers and recommend places to each other — or do they only browse?
02
Will businesses pay?
When Glow shows a salon real, measured consumer intent — views, calls, directions — does that convert into a paid placement?
03
Does the loop compound?
Do businesses distribute Glow to the customers already in their chair, while Glow sends new discovery back to them?

Beauty is personal.
The knowledge around it
shouldn't disappear.

Millions of beauty decisions happen across India every day — asked in group chats, answered by friends, and then lost. Glow turns them into something searchable, useful, and eventually intelligent.

Starting in Bangalore.
Built for India.

Investor conversations open