A working data platform for GTA transit.
QuantumLane ingests public transit feeds, persists them across a hot/cold storage split with proper schema and quality controls, exposes them via a read-only API, and surfaces its own operational health. The point isn't the dashboards — it's the engineering. Read the architecture →
Live status
Updated continuously. See full freshness page →
Ask it in plain English
Talk to QuantumLane through Claude or ChatGPT.
QuantumLane runs a public MCP server. Connect it to your AI assistant and ask about Toronto transit in plain language — "Where are the King streetcars right now?" — and it answers from live data. No code, no API keys.
The demo shows the difference: without the MCP, the assistant can't see live vehicles; with it, it answers in real time.
How to connect →What's flowing right now
Per-feed freshness, lag, and ingestion rates. Updated continuously from the same telemetry the operator uses.
What you can ask it
Pre-canned queries with the SQL shown alongside. Live data over the public API.
How it stays healthy
The architecture, the trade-offs, and the decisions that were rejected and why.