ChargeSite
AI-optimized EV charging location planning from grid, traffic, and usage data
The Problem
Billions are being spent on EV charging infrastructure. Location selection is based on real estate availability, not demand modeling. 40% of public chargers sit underutilized while drivers queue at the other 60%.
Why You Win
You understand grid constraints, vehicle energy consumption models, and the traffic patterns that actually predict charging demand versus the ones that look good in a PowerPoint.
Solo Founder Path
Combine traffic data, grid capacity maps, and existing charger locations. Build a demand-weighted site scoring model. Sell to charging point operators making $500K+ location decisions.
How AI Agents Scale It
AI agents continuously update demand forecasts, model grid evolution, score candidate sites in real-time, and optimize entire charging networks.
Market Background
The electrification and EV segment represents a $3.5B market opportunity. Billions are being spent on EV charging infrastructure. 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
Consumer battery reports only, no B2B tooling
Charging infrastructure, not software analytics
Charging network operator, not technology provider
YC Companies in Adjacent Space
Funded startups solving related problems — proof the market is real.
Find the most profitable sites to build EV charging stations
Data-driven EV charging site selection using profitability metrics — directly the same problem space as ChargeSite.
Streamline EV charger installations for real estate developers
Manages EV charger site development and installation — charge point site selection is upstream of the installation process Overflux handles.
We make EV charging as simple and reliable as LED lights
EV charging infrastructure for commercial locations — charge site selection determines where platforms like AmpUp deploy their solutions.
Moat Analysis
Domain Knowledge advantage specific to ChargeSite: deep automotive expertise encoded into product logic
Data Network Effects advantage specific to ChargeSite: each user interaction improves the system for all users
Switching Costs advantage specific to ChargeSite: integration depth and workflow dependency create stickiness
Regulatory Complexity advantage specific to ChargeSite: constantly evolving standards require continuous domain expertise
Proof & Signals
AI-optimized EV charging location planning from grid, traffic, and usage data. Growing market demand driven by industry transformation and AI adoption. LinkedIn posts about electrification automation consistently generate high engagement in automotive engineering circles.