Flow offers a digital twin platform for transit systems that delivers detailed ridership and on‑time performance data for every line and station. By providing highly reliable origin‑destination matrices and demand forecasts, it enables transit operators to optimize service frequencies, adjust routes, and improve resource allocation, leading to more efficient and customer‑focused mobility.
Funding
$17.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Transit agencies often rely on fragmented or outdated data sources, making it difficult to understand real-time ridership patterns and on‑time performance across lines and stations. This limits their ability to adjust service frequencies, redesign routes, or allocate resources efficiently, leading to suboptimal passenger experience and higher operational costs.
Solution
Flow offers a digital twin platform that continuously models transit systems by integrating diverse mobility data sources and applying advanced machine learning. The platform delivers granular ridership counts, on‑time performance metrics, and origin‑destination matrices for every line and station. Planners can use built-in forecasting tools to predict demand and simulate service changes before implementation. Insights are presented through an interactive dashboard that supports scenario analysis, enabling data‑driven adjustments to frequencies, routes, and schedules. The solution also provides customer‑behavior analytics and supports partnership data sharing with urban planners, researchers, and app developers.
Target Audience
Primary users are operational planners and transport operators at public transit agencies who need detailed mobility intelligence to optimize service delivery, as well as transport planners and urban policymakers responsible for network design and demand management.
Features
- Real‑time, line‑ and station‑level ridership and punctuality data aggregated from multiple public and private mobility sources
- High‑resolution origin‑destination matrices generated via machine‑learning algorithms for precise travel‑pattern analysis
- Demand forecasting models that project future ridership under various service scenarios
- Interactive dashboard for scenario simulation, service optimization, and performance monitoring
- API access for external partners to integrate mobility insights into planning tools, research projects, or consumer applications
- Continuous, cross‑border data updates leveraging a network of partners in 14 countries