Vision Document · Consumer Value Fund

The Default Capital Layer For India's Best Consumer Cohorts

A USD 100M non-dilutive financing vehicle for proven, measurable consumer growth pockets in India — cohort-driven capital secured against future revenues, designed to sit alongside VC structures.

00

The CVF Thesis

Situation

India's digital consumer stack now has enough attribution, repeat behavior, and payment maturity for cohort-level financing to be real rather than theoretical.

Complication

Founders with profitable paid channels still fund growth with the most expensive capital in the stack: new equity, broad venture debt, or internal cash they cannot spare.

Resolution

Build a VC-linked but operationally independent vehicle that finances only the cohorts already proving out — then monitors and resizes exposure in real time.

Fund Size
$100M
Target ARR
$2–20M
Performance Fee
9–12%
Hard Filter
No B2B · No RMG · No weak cohorts

What this is not: generic venture debt, broad startup credit, or a company-level growth loan. What this is: a specialist financing layer for India-domiciled consumer businesses where LTV:CAC, paid acquisition, retention curves, and repeat behavior are already visible enough to underwrite. Capital follows the proven channel. The fund resizes in real time. Repayment is cohort-performance-linked, not covenant-driven.

01

Why CVF Should Exist Now

India's digital consumer economy has reached an inflection point. Five converging forces create the right moment for specialized cohort-driven financing.

🌐 Digital Infrastructure Ready

500M+ active internet users. 90% UPI penetration in metros and tier-2 cities. AppsFlyer, Adjust, and Branch normalize attribution discipline at scale.

📊 Cohort Economics Now Measurable

For the first time, India consumer companies have clean real-time attribution of LTV, CAC, and retention. 2–3 years of cohort data now available across categories.

👥 Founders Capital-Constrained

Not idea-constrained. India consumer startups have proven PMF at 50M+ users, $2–20M ARR. They need capital to scale proven channels, not validate products.

💼 VCs Overdeployed in Equity

Portfolio companies need growth capital, but VCs can't do another round. A complementary non-dilutive sidecar unlocks existing portfolio quality without further dilution.

Founder gets

Non-dilutive capital tied to actual performance. Scale the winning channel without giving up equity or covenants that don't fit the business.

VC gets

Extends prior diligence. Portfolio companies grow without forcing equity at an awkward moment. Sidecar preserves VC relationships without overextending.

Capital provider gets

India consumer exposure. Not equity risk — short-duration returns tied to measured cohort behavior with real-time data, not quarterly storytelling.

02

Why VC-Linked Model Wins

Standalone venture debt fails on five structural dimensions. A VC-linked CVF overcomes each one.

Dimension CVF Advantage Standalone Debt
Sourcing ✓VC network, warm intros. 60–80% founder response rate. ✗Cold outbound. <10% response rate. High CAC.
Due Diligence ✓Inherits months of VC diligence on founder quality and market. ✗Cannot verify founder quality. Expensive from scratch.
Covenants ✓Real-time cohort monitoring. Founders cannot fabricate data. ✗P&L covenants. Lagging signal. Easily gamed.
Data Access ✓Founders share sensitive cohort data via VC trust. ✗Founders guard data from external lenders.
Alignment ✓Aligned on company success and VC exit economics. ✗Optimizes for fee extraction over company health.
03

Mechanics, Not Metaphors

Click the nodes below to inspect each stage — what matters, what gets measured, and where the real control points sit.

repayment + redeployment Source VC + market signals Underwrite cohort, not company Structure term sheet + controls Deploy channel-specific capital Monitor resize in real time
03.5

The Sourcing Ecosystem

Sourcing is the single most important operating system for CVF. Great underwriting cannot salvage a bad company — great sourcing discipline ensures only high-conviction opportunities reach the underwriting queue. Below is the full engine: three phases that compound on each other over time, feeding a single qualified pipeline into underwriting.

Sourcing Engine — click any zone to explore
PHASE 1 · PUBLIC SOURCING PHASE 2 · PRIVATE PARTNERSHIPS PHASE 3 · QUALIFY + DEPLOY 📱 App Store 30–50 companies 💰 Funding News 30–50 companies 📢 Ad Libraries 20–30 spenders 📊 Benchmarks Category insight Watchlist 80–120 companies · Week 6 Weeks 1 – 6 qualified 🤝 VC Portfolios 5–10 fac/yr 📊 MMPs 5–12 fac/yr 📱 Agencies 5–20 fac/yr 💳 Payments 3–20 fac/yr 👥 Founder Flywheel 70–80% conversion · activates Month 12+ referrals feed back Month 3 – 18 screened S1 Prelim Screen 60–70% pass S2 Intelligence 70–80% pass S3 Outreach 40–50% pass S4 Data Request 70–80% pass Underwriting Queue 10–12 qualified from every 100 sourced companies Ongoing

Click any zone or use tabs below to explore each phase in detail

Five parallel channels running from Week 1. Combined output: 80–120 de-duplicated candidate companies by end of Week 6. The goal is to enter any VC or MMP conversation with a credible watchlist already built.

Week-by-Week Journey Map
W1
Tool Setup
Create accounts: data.ai, Crunchbase, Meta Ad Library, Semrush. Document search criteria per channel.
→ Filters ready
W2
First Searches
Run searches across all 5 channels simultaneously. App Store top 100s, funding alerts live, Ad Library scans.
→ 50+ raw leads
W3
Consolidate
Master spreadsheet. De-duplicate companies appearing across multiple sources. Assign H/M/L confidence score.
→ 80–100 unique
W4
Deep Research
Founding team research, ARR triangulation (funding × multiple, install × ARPPU). Warm intro path mapping.
→ Profiles built
W5
Outreach Prep
Rank top 100–150 companies. Draft email templates per category. Set up Airtable pipeline. Identify warm intro paths.
→ Pipeline live
W6
Launch
Go live on outreach. Expect 10–15% cold response rate. Prioritise warm intros. Track every reply in CRM.
→ 10–15 convos
Total Watchlist
100–150
companies with profiles by Week 6
Active Conversations
10–15
founders interested in learning more
Cold Response Rate
10–15%
vs 30–50% via warm intro
LP Pitch Signal
50+
identified before fund close
The 5 Public Sourcing Channels
📱
App Store Intelligence

Top 100 games per subcategory. Filter: 10M+ installs, 4.0+ rating, monthly updates, founded 1–3 years ago. Cross-reference developer against Crunchbase to map VC backing.

data.ai Sensor Tower Mobile Action
Output: 30–50 gaming candidates
💰
Funding Announcements

Scan Series A/B announcements for India consumer companies in USD 2M–15M range. Map investor names to identify VC intro paths. Set up keyword alerts via VCCircle, Inc42, YourStory daily.

Crunchbase AngelList Inc42
Output: 30–50 funded candidates
📢
Ad Library Analysis

Active ad spend = active UA. Scan Meta Ad Library and Google Ads for India consumer companies running acquisition at scale. Consistent month-over-month spend signals optimized, profitable channels — not just experimentation.

Meta Ad Library Google Transparency Semrush
Output: 20–30 active UA spenders
📊
Benchmarking & Reports

Category reports tell you which verticals are growing and what LTV, CAC, and retention should look like. Filter your watchlist against these benchmarks before outreach — companies whose claimed metrics are wildly above category norms are a red flag.

Newzoo App Annie Business of Apps
Output: Category strategy doc
🌐
Ecosystem Databases & Operator Networks

MCA, NASSCOM, Startup India Portal, Product Hunt, Indie Hackers, and industry-specific Slack communities surface companies with formal structures. Breadth channel — less validated per company, but widens the funnel before private partnerships activate. A company listed on Startup India with an active founder on Indie Hackers is more likely to engage than a cold name from a list.

MCA.gov.in NASSCOM Product Hunt Indie Hackers Startup India
Output: 20–30 additional candidates (low-to-medium validation)

Public data gets you 80% of the opportunity. The final 20% — where deal quality is won or lost — requires private access to verify revenue, validate cohort quality, and confirm founder execution ability. Five partnership layers activate in sequence over months 3–18. The fifth layer (founder referrals) creates the self-compounding flywheel.

Layer 1 · Core Engine · Months 1–3
🤝 VC Portfolio Access
5–10 fac/yr +

VCs have spent months on due diligence. Founders in their portfolios have already been screened for capability. VCs have board seats and data access — they can vouch for company quality and have incentive to support their portfolio. Formalise 3–5 VC relationships in months 1–2. Request warm intros to portfolio companies that fit CVF criteria. Share aggregated portfolio benchmarks back as a value-add.

VC Partners Target
3–5
India-focused consumer VCs
Fits per VC
3–5
viable companies per partner
Conversion Rate
30–50%
vs 10–15% cold outreach
Layer 2 · Data Moat · Months 3–6
📊 MMP & Attribution Partners
5–12 fac/yr +

AppsFlyer, Adjust, Branch, Singular see acquisition and retention data for most major app-based companies. They know which customers are spending on UA at scale and which have healthy cohort behavior — before CVF does. Partnership provides aggregated benchmarks by category (top 50 gaming apps by cohort quality) and warm intros to high-performing customers. MMP's endorsement raises CVF's credibility dramatically with founders.

MMP Partners
2–3
AppsFlyer, Adjust, Branch
Referrals/MMP/yr
5–10
companies per partner
Conversion Rate
40–60%
MMP endorsement lifts trust
Layer 3 · Scale Channel · Months 4–6
📱 Agencies & Media Buyers
5–20 fac/yr +

Agencies see first-hand which clients have healthy unit economics and which don't. Target 10–15 mobile app acquisition agencies in India specialising in gaming, fintech, ecommerce. The incentive is aligned: if clients grow faster with CVF capital, agency billings grow. Co-marketing makes CVF part of the agency's pitch to new clients — "we help clients optimise AND access non-dilutive capital."

Agency Partners
5–10
media buying + growth agencies
Referrals/Agency/yr
3–5
client companies per agency
Conversion Rate
30–40%
agency vouch improves trust
Layer 4 · Payment Signal · Months 5–8
💳 Analytics & Payment Processors
3–20 fac/yr +

Razorpay and Stripe see transaction patterns. Mixpanel and Amplitude see user engagement and repeat behavior in real time. Companies with monthly revenue growth >50% and repeat transaction rate >30% surface naturally. Cross-reference this signal list against your public watchlist and VC portfolio data — overlap means high confidence. Companies on all three lists are priority outreach.

Key Partners
Razorpay · Stripe · Mixpanel · Amplitude
Signal to watch
MoM revenue >50% + repeat rate >30%
Layer 5 · Flywheel · Month 12+
👥 Founder & Operator Referrals
14–40 fac/yr +

The highest-conversion sourcing channel and the last to activate. Founders in CVF's funded network refer other founders — 70–80% conversion rate, dramatically higher than any other channel. This flywheel activates after the first 10 facilities are live. Quarterly founder dinners and a referral incentive programme (discounted terms for referring companies that get funded) accelerate it. Over time, this layer becomes self-sustaining.

Conversion Rate
70–80%
highest of any channel
Referrals/Founder/yr
2–5
per funded founder in network
Activates After
10
facilities deployed

From sourced company to underwriting candidate — a four-stage gate process with defined pass rates and rejection criteria at each stage. The discipline here is as important as the sourcing volume: a fast no saves everyone time. Only ~10–12% of sourced companies reach formal underwriting, and that is by design.

S1
Preliminary Screen
5 gates — all must pass: India-domiciled, consumer model, $2–20M ARR, priority category, actively seeking growth capital.
60–70% pass
~65 from 100
S2
Intelligence Layer
Founding team, business model, market position, growth trajectory, ARR triangulation (funding multiple, install × ARPPU, traffic × conversion).
70–80% pass
~50 from 65
S3
Outreach & Conversation
Warm intro preferred (30–50% conv). Cold outreach (10–15%). 20-min exploratory call: which channel is most profitable, do they have 6+ months cohort data, are they open to non-dilutive capital?
40–50% forward
~22 from 50
S4
Data Request
Standard template: 12–24 months cohort acquisition + revenue data. Hesitation at this stage is a red flag — founders with clean data share it within 2 weeks. 70–80% who share data qualify for formal underwriting.
70–80% qualify
10–15 to underwriting
Conversion Path — Every 100 Sourced Companies
100 sourced → 65 screened → 50 validated → 22 conversations → 15 data requests → 10–12 underwriting
Timeframe Companies Sourced Facilities/yr Active Layers
Year 1 100–150 10–15 Public sourcing + 3–5 VC partnerships
Year 2 200–300 20–30 VC + MMP + Agencies + first founder referrals
Year 3+ 400–600 40–60 All 5 layers + founder flywheel at scale
04

Where the Fund Starts, and Where it Waits

Categories ranked by underwriting readiness and launch sequence. The fund starts with proven payback loops, then phases into adjacent verticals.

Tier 1: Immediate Focus (Launch Wedge)
Tier 1 — 40% of Capital
Gaming (Casual & Mid-Core)
200+ studios with proven unit economics. Cohort metrics mature. Repayment logic straightforward. Operators already think in CAC and payback windows.
Casual M1 Retention
> 20%
LTV:CAC
> 2.5x
Payback
6–9 months
ARR Range
$500K–10M
Tier 1 — 25% of Capital
Ecommerce & D2C
Strong cohort economics. Repeat purchase behavior measurable. Repayment tied to repeat revenue. Must underwrite net of returns, refunds, and fulfillment.
Repeat Purchase Rate
> 25%
Repeat LTV:CAC
> 3x
Gross Margin
> 40%
ARR Range
$1–15M
Tier 1 — 20% of Capital
Digital Subscriptions
Recurring revenue ideal for performance facilities. Cohort economics stable. Churn curves predictable. Acquisition discipline matters more than broad TAM story.
Month 1 Retention
> 50%
Month 3 Retention
> 30%
LTV:CAC (12mo)
> 3x
ARR Range
$2–20M
Tier 2: Scale Phase (Year 1–2) — Conditional Entry
Tier 2 — Phase In
Fintech & Insurance
High-LTV acquisition measurable. Regulatory evolving. Longer payback periods. Works where repeat usage and renewal behavior are strong. Needs net-of-cancellation proof.
Readiness
●●●○○
Signal Quality
●●●○○
Entry Gate
Year 1+
Risk
Policy-sensitive
Tier 2 — Second Wave
Travel & Hospitality
Repeat demand and digital funnels visible. Timing effects and seasonality are harder to model. Refund complexity requires conservative underwriting.
Readiness
●●●○○
Signal Quality
●●●○○
Entry Gate
Year 2+
Risk
Seasonality
Tier 3: Future Expansion / Hard Exclusions
Tier 3 — Wait
Hyperlocal
Potentially interesting but too execution-heavy for the opening strategy. Keep off the opening map until the vehicle has stronger playbooks and operating leverage.
Readiness
●●○○○
Signal Quality
●●○○○
Status
Wait
Issue
Ops-heavy
Tier 3 — Wait
Creator Economy
Interesting upside but monetization and repeatability are still inconsistent. Could become relevant later, not before the fund proves discipline in measurable categories.
Readiness
●○○○○
Signal Quality
●○○○○
Status
Wait
Issue
Weak repeatability
Hard Exclusions — Do Not Pursue
Out-of-Scope Segments
B2B, real-money gaming (RMG), heavily offline businesses, and weak-cohort models remain permanently out of scope. The point of the vehicle is to stay disciplined — these categories break the logic rather than stretch it.
CVF Investment Universe
Illustrative positioning — payback period vs LTV:CAC ratio. Bubble size = relative ARR. Hover dots for details.
Gaming Ecommerce Subscriptions Fintech Travel Below threshold
1× 2× 3× 4× 5× 6× 0 3mo 6mo 9mo 12mo 15mo 18mo CAC PAYBACK PERIOD LTV:CAC CVF SWEET ZONE 3–9mo · 2.5–5× LTV:CAC
05

Underwriting Framework

Linear 5-stage process. Click any stage to see what matters, what gets measured, and who decides. Funnel stages switch between Deployment and Underwriting views.

Source VC + market Screen Data quality Structure Term sheet Deploy Capital out Monitor Real-time

Click any stage to inspect what matters and who decides

06

Operating Model & Phased Rollout

Four-phase build sequence over 60 months. Each phase validates assumptions before unlocking the next scale point.

Phase 1 · Months 1–6
Foundation

2-3 pilot facilities. $20-30M first close. Hire underwriting spine. Monitoring live from day one.

Phase 2 · Months 7–18
Validation

Scale to 15-25 active facilities. Develop category playbooks. 70%+ cohorts at forecast.

Phase 3 · Months 19–36
Maturation

50+ active facilities. Add data partnerships. $80-100M deployed. Repeat facility rate 20%+.

Phase 4 · Months 37–60
Optimization

12-15% net IRR in range. Management + performance fee model proven. Plan CVF II.

07

Governance & LP Protection

Five institutional pillars ensure capital preservation and interest alignment. Click any pillar in the mind map — or the cards on the right — to expand details.

5-Pillar Governance Model — click any node

CVF Governance Gov. Architecture Data & Monitoring Capital Controls LP Protection Risk Management

Expanded Pillars

Governance Architecture +
Investment Committee: Head of CVF + 2 independent board members. Monthly reviews on facility approvals and sizing.

Board Structure: Founder-led operations + independent board chair. Quarterly board meetings.

LP Advisory Board: Optional investor participation with monthly briefings on category strategy.
Data & Monitoring +
MMP Integration: Real-time API feeds from AppsFlyer, Adjust, or Branch. CVF maintains independent data warehouse — no reliance on founder data for underwriting.

Fraud Detection: Automated alerts for abnormal install patterns, retention cliff drops. Quarterly fraud audits.

Dispute Resolution: 5-day SLA. CVF's MMP data is authoritative if disagreements arise.
Capital Controls +
Facility Sizing: Finance 6-12 months of best-performing channel only — not blended budgets.

Performance Fee: 9-12% annualized depending on risk and payback period.

Control Points: Automatic resizing if CAC increases or retention drops. Clawbacks if capital diverted to non-approved channels.
LP Protection +
Return Waterfall: (1) Return of capital; (2) Preferred return 8-10% annually; (3) 70/30 carry split (LP/CVF).

Diversification: 50-100 active facilities — no single company >5% of capital.

Monthly LP Reports: Deployment pace, write-downs, collections, and return projections.
Risk Management +
Diversification: 50-100 companies, 100+ cohorts. No single company >5%, no single channel >30%.

Stress Testing: All facilities pre-approved against +20% CAC, -10% retention, +10% refunds.

Escalation: Real-time alerts → monthly deep dives → quarterly strategic reviews.
08

Risks & Mitigations

CVF manages three risk categories through diversification, real-time data, and active engagement.

Risk Type What breaks Mitigation
Category Shock One sector loses profitability due to platform change or competition. ✓Diversify across 5+ categories. Reallocate fast when economics break.
Data Quality Attribution and revenue data noisy or manipulated. ✓Require minimum MMP maturity. Monitor continuously, not quarterly.
VC Concentration Too much sourcing dependence on one partner. ✓VC-linked, not VC-owned. Widen funnel through MMP, agency, CFO channels.
Macro Slowdown Consumer spending compression pressures LTV across the book. ✓Short payback windows. Conservative pricing. Stage + category diversification.
Execution Drag Small team becomes bottleneck without systematized playbooks. ✓Build data stack and underwriting templates early. Operating efficiency as moat.
Deployment · Stage 1
Source Quality, Not Volume
Sourcing starts with VC portfolios and operator networks — not outreach lists. The edge is inherited signal: VCs already know which founders measure cleanly and which channels perform.
Primary source
VC portfolio warm intros
Pass signal
6+ months cohort data available
Owner
Head of Sourcing
Deployment · Stage 2
Initial Screening
Quick data quality check. Reject immediately if: no MMP attribution, no 6-month history, LTV:CAC below 1.5x stressed, or founder unfamiliar with cohort economics. Fast no saves everyone time.
Pass rate
~70% of sourced
Timeline
1 day
Hard reject signals
No MMP, no cohort history, LTV:CAC <1.5×
Deployment · Stage 3
Term Sheet & Facility Design
Structure the facility against the best-performing channel only — not blended budgets. Set performance fee 9-12% based on payback period and category risk. Define resizing triggers and clawback conditions before capital moves.
Timeline
3-5 days
Fee range
9-12% annualized
Authority
Head of CVF or Committee
Deployment · Stage 4
Capital Deployment
Capital deploys same day after signing. MMP data feeds go live immediately. Company executes on approved channel only. First weekly review scheduled at signing. Start conservative — 60-80% of current channel spend.
Speed
Same day after signature
Deployment start
60-80% of channel spend
First review
Week 1
Deployment · Stage 5
Continuous Monitoring
Weekly CAC and retention tracking via MMP data. Monthly deep-dive with founder. Automatic alerts if M1 retention drops 10%+ or CAC increases 20%+. Resize before problems become defaults. Repayment feeds the next cohort cycle.
Cadence
Weekly data, monthly review
Alert threshold
M1 -10%, CAC +20%
Action
Resize or escalate to committee
Underwriting · Stage 1
Data Pack Request
Standard template request: acquisition date, channel, CAC, M1-M12 retention, revenue by month, net of refunds. 12-24 months of history required. Founders who can't supply this in 2 weeks fail the data readiness test.
History required
12-24 months
Timeline
1-2 weeks from request
Pass rate
~80% of screened
Underwriting · Stage 2
Cohort Analysis & Stress Testing
Model payback curves and LTV:CAC by channel. Validate retention stability. Stress test: what happens if CAC increases 20%, M1 retention drops 10%, refunds increase 10%? LTV:CAC must hold above 1.8x stressed.
Analysis period
1-2 weeks
Pass threshold
LTV:CAC >1.8× stressed
Pass rate
~50% of data packs
Underwriting · Stage 3
Risk Assessment
Category-specific risk scoring: competitive risk, platform risk, founder risk, macro sensitivity. Define exact covenant thresholds for this facility. Must achieve risk-adjusted IRR above 10% before moving to committee.
Duration
1 week
Pass threshold
Risk-adj. IRR >10%
Key input
Category benchmarks
Underwriting · Stage 4
Investment Committee
Present full analysis: cohort data, stress tests, risk factors, facility structure, and recommendation. Committee votes: Approve / Approve with Conditions / Decline. Weekly or bi-monthly cadence. Only ~15-20% of assessed deals reach approval.
Cadence
Weekly or twice monthly
Approval rate
~15-20% of assessed
Decision time
1 week
Underwriting · Stage 5
Term Sheet & Execution
Final term sheet agreed. Legal review 3-5 days. Facility agreement signed with all covenants and monitoring thresholds formalized. Capital deploys same day as signature. Monitoring begins immediately.
Legal review
3-5 days
Capital deployment
Same day after signature
Next step
Deployment Stage 4 begins