EmissionsGap
Real-world versus type-approval emissions monitoring for fleet compliance
The Problem
Real-world emissions can be 2-7x higher than type-approval values. Regulators are moving toward Real Driving Emissions monitoring. OEMs and fleets need to track the gap but have no continuous measurement outside the test cell.
Why You Win
You understand emissions calibration, the gap between NEDC and WLTP, and why lab values systematically diverge from reality in predictable ways.
Solo Founder Path
Build a fleet-connected emissions estimation tool using OBD-II lambda, MAF, and fuel injection data. Validate estimates against portable emissions measurement data.
How AI Agents Scale It
AI agents process fleet-wide driving data, flag compliance risks per vehicle, and generate regulatory reporting packages automatically.
Market Background
The vehicle data and analytics segment represents a $4B market opportunity. Real-world emissions can be 2-7x higher than type-approval values. Early movers building AI-native solutions in this space can capture significant market share before incumbents adapt their legacy offerings.
Tech Stack
12-Week Roadmap
Pricing Ladder
Limited usage to evaluate the product. See what AI-powered automation looks like.
Full core features, standard integrations, email support.
All features, priority support, multi-project dashboard, API access.
SSO, on-prem option, custom integrations, dedicated support, SLA.
Competitive Landscape
Fleet telematics platform, not automotive-specific analytics
Industrial AI platform, not automotive-focused
Driver safety AI, narrow vehicle data scope
YC Companies in Adjacent Space
Funded startups solving related problems — proof the market is real.
We help companies automate the accounting of their carbon emissions
Automates emissions tracking for high-emission industries — directly adjacent to vehicle emissions compliance monitoring.
Enterprise software for companies to track and reduce their carbon emissions
AI/ML-powered supply chain carbon tracking across 48+ countries — automotive emissions compliance requires similar cross-border tracking.
Moat Analysis
Domain Knowledge advantage specific to EmissionsGap: deep automotive expertise encoded into product logic
Data Network Effects advantage specific to EmissionsGap: each user interaction improves the system for all users
Switching Costs advantage specific to EmissionsGap: integration depth and workflow dependency create stickiness
Regulatory Complexity advantage specific to EmissionsGap: constantly evolving standards require continuous domain expertise
Proof & Signals
Real-world versus type-approval emissions monitoring for fleet compliance. Growing market demand driven by industry transformation and AI adoption. LinkedIn posts about data automation consistently generate high engagement in automotive engineering circles.