Vecarta turns parking into a data-driven asset by using AI to analyze satellite and street-level imagery, eliminating the need for physical sensors or manual field counts. The platform provides block-level and hourly occupancy data for on-street and off-street spaces, enabling cities and consultants to price, manage, and plan parking with verifiable evidence. It delivers reports in days, not months, and tracks variance to the ideal 85% occupancy rate.
Funding
Funding not disclosed
Founders
Product
Problem
Traditional parking occupancy surveys rely on manual field counts or expensive, hardware-based sensor networks that require installation and ongoing maintenance. These methods are labor-intensive, costly, and often impractical for cities and businesses outside major downtowns, limiting their ability to make data-driven parking decisions.
Solution
Vecarta provides a Virtual Parking Survey platform that uses AI to analyze historical and current satellite and street-level imagery, counting occupied versus vacant spaces by block and hour. This asset-lite approach eliminates the need for sensors or field crews, delivering accurate occupancy data for lots, curbs, and entire districts globally. Clients share their area of interest, and Vecarta processes the imagery to produce actionable reports on parking demand, utilization, and variance from the ideal 85% occupancy rate. The platform supports one-time studies or ongoing monitoring, enabling governments and consultants to price, manage, and reform parking policies with verifiable, block-level data.
Target Audience
Primary customers are local government transportation officials and parking consultants who need accurate, scalable parking occupancy data for planning, pricing, and policy reform without the cost of sensor infrastructure.
Features
- AI-powered analysis of satellite and street-level imagery to count occupied vs. vacant spaces by time of day and day of week
- No hardware installation or maintenance required, reducing costs and deployment time
- Covers on-street, off-street, lots, and districts globally, with reports delivered in days
- Tracks occupancy variance to the ideal 85% rate, supporting dynamic pricing and demand management
- Enables instant inventory of parking assets, monitoring of commute behavior, and forecasting of future needs
- Provides before-and-after impact analysis for policy changes, backed by block-level, time-of-day data