Reroute is a multimodal travel app that calculates the fastest door‑to‑door route by combining driving, parking at GO stations, and public transit, and ranks each option based on real‑time conditions. It integrates live service alerts and an ML model trained on over 390 k TTC delay records to avoid risky lines, while its built‑in AI assistant Miles lets users ask natural‑language queries like “best way to Union at 5?” and receive a mapped plan.
Funding
Funding not disclosed
Founders
Product
Problem
Commuters in the Greater Toronto Area must choose between separate driving, parking, and transit apps, which do not evaluate combined door‑to‑door travel time or incorporate real‑time service disruptions. Existing tools either focus on a single mode or lack predictions for transit delays, leading to suboptimal route choices.
Solution
Reroute delivers a single web app that computes the fastest door‑to‑door itinerary by evaluating pure driving, pure transit, and hybrid drive‑to‑park‑and‑ride options. The platform ranks each alternative using live traffic data, transit schedules, and real‑time vehicle positions refreshed every 15 seconds. An integrated AI assistant, Miles, accepts natural‑language queries, generates a complete route, and explains the trade‑offs between modes. Service alerts from the entire transit network are embedded in the ranking, and a machine‑learning model trained on 393,303 TTC delay records flags lines that are likely to experience problems before the user boards. The result is an honest, agency‑independent recommendation that updates automatically as conditions change.
Target Audience
Primary users are commuters and travelers in the GTA who need accurate, multimodal door‑to‑door routing, and developers who want to embed Reroute’s routing engine and delay‑prediction model via an API.
Features
- Hybrid routing that combines driving to a GO station, parking, and onward transit, compared against pure driving and pure transit options
- Real‑time ranking based on current traffic, live vehicle locations, and up‑to‑date transit schedules
- Machine‑learning model predicting TTC line delays using over 390 k historical delay records
- Integrated service‑alert board that lowers the rank of routes touching disrupted lines and automatically suggests alternatives
- AI assistant Miles that processes plain‑language requests, creates the itinerary, and explains mode trade‑offs within the app
- Live vehicle position updates every 15 seconds for accurate travel‑time estimation
- Privacy‑first design: no user accounts, route queries and AI messages are discarded after processing, and only minimal anonymous identifiers are stored locally