# Cartgraph AI: The Global Commerce OS for Brands
> Discover how Cartgraph AI uses agentic intelligence to automate cross-border e-commerce, from demand detection to advertising and global scaling.

Tags: ai, e-commerce, startup, cross-border-trade, agentic-ai, marketing-automation, global-commerce, pitch-deck
## Slide 1: Cartgraph AI - The Global Commerce OS
* Cartgraph AI is an agent network running cross-border brands end-to-end as an autonomous commerce brain.

## Slide 2: Why Now?
* AI decision costs dropped 90% in 24 months.
* Cross-border commerce is reaching escape velocity with 59% of shoppers buying internationally.
* India is emerging as a global D2C export hub with 14% YoY growth.

## Slide 3: The Sheer Opportunity
* Global e-commerce market estimated at $6.8T - $8T.
* Cross-border e-commerce expected to reach $1.2T by 2027.
* Current brand stacks are fragmented, often requiring 12 different agencies.

## Slide 4: The Broken Stack
* Launching a product currently takes 60+ days across multiple vendors for research, creative, and ad management.

## Slide 5: Market Opportunity
* Total Addressable Market (TAM): $2.1T global cross-border e-commerce.
* Serviceable Obtainable Market (SOM): $12B AI intelligence layer.
* Focus on the India-US corridor growing at 35% YoY.

## Slide 6: The Thesis
* Cartgraph aims to do for commerce what YouTube did for creators: enabling any product to go global instantly.

## Slide 7: The Solution - Two AI Agents
* **ARIA (Marketing Brain):** Runs ads, pricing, and localization.
* **SCOUT (Demand Radar):** Finds unmet demand and generates sourcing briefs.

## Slide 8: How It Works
* A continuous learning loop where SCOUT identifies demand and ARIA executes campaigns, with data feeding back into the system.

## Slide 9: Product Layers
1. Data Layer (APIs, ads, reviews).
2. Intelligence Core (Pricing, forecasting).
3. Execution Layer (Creative generation, automation).
4. Command Center (Natural language control).

## Slide 10: The Intelligence Flywheel
* Network effects where more brands lead to better data, faster movements, and improved discovery via SCOUT.

## Slide 11: Competitive Landscape
* Cartgraph positions itself as a complete system/loop rather than a singular tool for research or ad optimization.

## Slide 12: The Moat
* Architecture: Unified system.
* Memory: Retained brand intelligence.
* Network Effects: Compounding advantages for all participating brands.

## Slide 13: Business Model
* Evolution from managed services (10-15% GMV) to a SaaS + Revenue Share model ($500-$2,500/mo + 8-12% GMV).

## Slide 14: Go-To-Market Strategy
* Phase 1: Amazon US (Health, Beauty, Home).
* Phase 2: Multi-channel (Walmart, Target, TikTok).
* Phase 3: Global markets (Europe and Asia).

## Slide 15: Roadmap to Scale
* Targeting $200M GMV and 500 brands by late 2027.

## Slide 16: The Team
* Led by Ritesh Srivastava (CEO, 21 years in retail) and Michael Wei (CTO/AI Lead, ex-Google, Postmates).
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