Investor Pitch Deck: Rerouting the Map
Semantic Search & Deflection Advertising in the POI Market
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We're excited to share our comprehensive investor pitch deck outlining Maei.ai's vision to transform the local search and advertising market. Discover how RAG-based semantic POI search and deflection advertising create a $15B market opportunity competing with Yelp and Google through conversational intent-based discovery and outcome-based pricing.
Key Highlights
Topics Covered
Overview
Our investor pitch deck presents a comprehensive vision for transforming the local search and advertising market through two core innovations:
1. Semantic Search
Replace keyword-based searches with natural language understanding powered by RAG (Retrieval-Augmented Generation) over a semantic POI knowledge graph. Users can express complex intents like "Quiet café with good WiFi for working, under $10, 5-min detour from my route" and receive personalized, contextual matches.
2. Deflection Advertising
Merchants bid to deflect your route by offering value that justifies the detour—not spam, but helpful suggestions at the right moment. This outcome-based advertising model aligns merchant interests with user value, creating a win-win marketplace.
The Market Opportunity
The local search advertising market represents a massive opportunity:
- $65B TAM — Global local search advertising (Google Local Ads + Yelp + Meta + others)
- $15B SAM — Route-aware, intent-driven search segment
- $750M SOM — Year 5 target with 5% market penetration
Current local search is broken. Users abandon 78% of searches due to information overload. Merchants waste $12B annually on non-converting impressions with geofence ads achieving only 0.5-1% conversion rates.
Why This Matters
Traditional local search platforms like Yelp and Google have dominated the market for over a decade, but they suffer from fundamental limitations:
- Keyword-based matching can't understand nuanced user intent
- Static rankings ignore user context, route, and real-time preferences
- Proximity-only filtering isn't route-aware or purpose-driven
- Review overload creates decision paralysis and abandonment
Our platform solves these problems through AI-powered semantic understanding, creating a new category of intelligent, conversational local discovery that puts users first while delivering better ROI for merchants.
Technical Foundation
Our competitive moat is built on four technical pillars:
1. Canonical POI Knowledge Graph
Structured entity relationships, taxonomies, and attributes enabling precise semantic matching
2. Multi-Modal Embeddings
Vector representations combining text (reviews, descriptions) and visual (menu photos, ambiance) signals
3. Real-Time Route Integration
Trajectory-aware filtering that understands your current route and acceptable detours
4. RAG Orchestration
Retrieval-Augmented Generation that transforms queries into personalized, contextual recommendations
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Goetz Weber
Contributor @ Maei.ai
Pioneer in motion intelligence, trajectory AI, and semantic routing. Theoretical physicist turned AI innovator.
Follow me on LinkedIn for insights on motion intelligence and AI