TenzorX 2026 · Problem 4C · Poonawalla Fincorp

See the Store. Know the Cash Flow.

Remote kirana underwriting through real-time computer vision — analyzing shelf density, SKU diversity, and inventory velocity from a single smartphone video.

No field visits  ·  No documents  ·  60-second decisions

Scroll to discover expand_more
NETWORK REACH
0
Kirana Outlets
MARKET SIZE
₹5.5L Cr
Annual Turnover
PROCESSING SPEED
0
Assessment Time
COST REDUCTION
0
vs Field Visits
THE BOTTLENECK

India's kiranas can't get loans because of the "Visibility Gap."

The cash flow is real. The data just doesn't exist on paper — yet.

menu_book

No Formal Books

Cash-based transactions and handwritten registers leave zero digital footprint for traditional banks to analyze.

UNVERIFIABLE DATA
distance

Field Visits Don't Scale

Each manual audit costs ₹800–₹1,200. At 13 million stores, that's ₹10,400 Crore just to assess everyone once.

NEGATIVE ROI UNIT ECONOMICS
psychology_alt

Gut Feel Isn't Credit Policy

Subjective officer judgment causes high NPAs and systemic bias against small-town retailers who deserve credit.

SYSTEMIC RISK
THE SOLUTION

KiranaLens.

A smartphone.

A new credit score.

1
Record

A 60-second video walkthrough of shop shelves. Any Android or iPhone. No special hardware.

2
Analyze

Edge-AI identifies SKU diversity, shelf density, inventory depth, refill velocity, and brand concentration in real time.

3
Score

Instant creditworthiness report with confidence bands — backed by visual evidence, not a field officer's gut.

AUDIT_ID: KL-9921-X
PRE-APPROVE
EST. DAILY SALES
₹18,400
REVENUE INDEX
0.92
RISK SCORE
AA+
FRAUD PROB.
0.02%
01{ "store_intel": {
02"shelf_occupancy": 0.88,
03"sku_count": 1420,
04"category": "High Premium",
05"refill_velocity": "High",
06"confidence": 0.91
07} }
Decision generated in 4.2s
VISION INTELLIGENCE

What the AI sees.

Four visual signals extracted from every frame.

01
SHELF DENSITY
85%

Volume utilization across main racking — proxy for working capital deployed.

02
SKU DIVERSITY
1,420

Unique product identifiers detected — signals footfall capture across customer types.

03
INVENTORY VALUE
₹4.2L

Stock-at-hand estimate using average market prices — fast-moving vs slow-moving mix.

04
REFILL SIGNAL
V.Fast

Void-pattern detection predicts replenishment rate — partially empty = recent demand.

CONTEXTUAL DATA

Hyper-local surroundings.

  • home_work
    Catchment Intel

    Population within 500m radius, residential vs commercial mix — demand baseline signal.

  • groups
    Footfall Density

    Road type, proximity to schools, offices, transport hubs → traffic multiplier for daily sales estimate.

  • radar
    Competitive Heatmap

    Nearby store count — moderate competition proves demand; excess compresses margins.

Sales = f( SDI · SKU · Inventory · Footfall · Competition · Area · Mix )
School 280m Bus Stop 90m Rival 160m
security ANTI-GAMING ENGINE

Built to be cheat-proof.

Every manipulation has a counter-signal. Every signal has a cross-validator.

FRAUD VECTOR 01
Shelf-Stuffing Detection

AI recognizes borrowed goods — multi-image temporal consistency check catches inventory that wasn't there yesterday.

DETECTED
FRAUD VECTOR 02
Location Bias Verification

Cross-referencing GPS metadata with architectural landmarks. High inventory in low-footfall geo = automatic flag.

DETECTED
FRAUD VECTOR 03
Borrowed Space Analysis

Visual area estimation vs GPS footprint discrepancy. Differentiates store-owned inventory from distributor transit stock.

DETECTED

Fraud resilience is a first-class feature, not an afterthought.

Every signal has a counter-signal. Every output is auditable.

BUSINESS CASE

Why Poonawalla Fincorp wins.

Cost per
Underwriting

BEFORE
₹1,200
WITH KIRANALENS
₹15

98.7% reduction in operational overhead.

Break-even at 1 prevented bad loan per 500 assessments.

Growth Impact

Portfolio Reach 100×
Disbursement Cycle 4h vs 7 days
NPA / Default Rate −30%
Addressable Market ₹39L Cr
UNDER THE HOOD

Simple. Scalable. Deployable.

Three-layer architecture. Production-grade from day one.

INPUT
iOS/Android SDK Video Stream Processor GPS / IMU Metadata
AI ENGINE
YOLOv10 Object Detection Google Vision API OCR Engine Geo Scoring (Maps API) Confidence Calibration
OUTPUT
REST API PDF Report Engine Lender Dashboard Webhooks
BUILT WITH React Node.js FastAPI YOLOv10 Google Vision Maps API MongoDB
TRY IT NOW

Every kirana store
deserves a fair shot.

KiranaLens turns a smartphone into a branch.
Every store in India becomes a bankable asset — in 60 seconds, from anywhere.

Built for Poonawalla Fincorp · TenzorX 2026 · Problem Statement 4C