Sponsorship Intelligence Infrastructure
Brands invest billions to connect with audiences through sports, music, gaming, and festivals. There is no shared data layer mapping these connections. We're building it. Starting with India.
Finance got Bloomberg in 1982. Recruiting got LinkedIn's talent graph. Real estate got MLS databases. Each time, the same pattern: a market built on relationships and information asymmetry gets a shared data layer and the entire industry restructures around it.
Global sponsorship is a $75 billion market. India's share alone is ₹16,633 crore, growing 44% annually. It runs on gut instinct, recycled pitch decks, and WhatsApp forwards. There is no shared data layer. No relational graph. No structured intelligence.
The information asymmetry isn't a feature of the market. It's a problem that hasn't been solved yet.
The atomic unit isn't the brand. It isn't the property. It isn't the community. It's the connection between them. Map all three, and collision intelligence, white space detection, territory maps, and category void analysis emerge automatically.
Gold-highlighted entities appear across all three cards. That's the relational structure. That's what we map.
A 6-minute check-in and a 6-hour deep session use the same data layer. The depth you need is always there — you choose how far in you go.
| Brand | Competitor | Shared Properties | Sector | Events |
|---|---|---|---|---|
| Coca-Cola India | PepsiCo India | IPL, ICC World Cup, PKL | FMCG / Beverages | 3 |
| Dream11 | CRED | IPL, ISL | Fintech / Gaming | 2 |
| Hyundai India | Mahindra | IPL, ISL, PKL | Automotive | 3 |
| Red Bull India | Monster Energy | BGMI Masters, Sunburn | Energy / Beverages | 2 |
| OnePlus India | iQOO | IPL, BGMI Masters | Consumer Tech | 2 |
| Bira 91 | Kingfisher | Sunburn, NH7 Weekender | Alc. Beverages | 2 |
Not just agencies. Not just brands. Anyone whose decisions depend on understanding where brand money flows and how cultural identity connects to commercial value.
Track every competitive move. Map your territory. Find white space before your rivals do.
Know what your inventory is worth. Identify category voids. See who's circling before they call.
Source properties with data, not rolodexes. Validate recommendations with competitive intelligence.
Size market structure, brand moats, and deal flow. Understand which brands have real cultural equity.
Artists, athletes, creators — understand your commercial value in the sponsorship ecosystem.
Map the cultural economy. Track sponsorship flows across sectors, properties, and communities.
In 2026, every major agency holding company built AI platforms on the same foundation models. WPP spent £300M. Dentsu went "AI-native." IPG automated 75% of media buying workflows. The differentiation wasn't the AI. It was the proprietary data underneath.
Every entity added creates new connections. 58 brands × 191 properties × 28 communities = a graph that compounds. The more edges, the more intelligence surfaces automatically.
No legacy architecture to "refound." Built on the assumption that AI reads the data layer, surfaces signals, and computes insights. The model, not the interface, is the product.
Not cricket sponsorship. Not music festivals. The entire brand × property × community graph — horizontal, relational, universal. Verticals are easier but less durable.
"The real moat is proprietary data, not AI models. Every holding company uses the same foundation models. The differentiation comes from proprietary data."
Pattern across 45+ industry sources, May 2026Live Intelligence
Real signals from the platform — auto-matched to entities in the graph.
resear.sh engages AI Agents, Human Domain experts who've worked in agencies who made these deals to guide these agents.
Get Started
resear.sh is in private beta. We're onboarding brand managers, IP owners, agencies, and investors who need structured sponsorship intelligence.