Build with RiskThinking.AI
Toronto Climate Week 2025
Join RiskThinking.ai during Toronto Climate Week (Oct 1–3, 2025) to prototype real solutions using RiskThinking.ai’s Climate Digital Twin (CDT™) via CDTexpress. Selected teams will advance to the in-person finale in Toronto, where a judging panel featuring Chris Hadfield, renowned Canadian astronaut and national icon, will select the winner.
Hackathon event showcasing climate risk analytics innovation

Why Join?

Who Should Apply?

Students, researchers, data scientists, engineers, product builders, and sustainability practitioners. Teams of 2–5 recommended (solo applicants welcome).

What We Provide

CDTexpress sandbox tenant with ample API credits

RiskThinking.ai Python SDK (pip installable)

Example notebooks that show common workflows

API documentation and quickstart guides

Slack/Email support during the build window and live office hours

CDTexpress Dashboard Interface

The Challenges

Select from one of the problem statements below

Asset-level Physical Risk & Adaptation Planner (Toronto focus)

Goal: Turn high‑resolution hazard and vulnerability data into actionable adaptation guidance for buildings or infrastructure in the GTA.


Build a prototype that:

  • Pulls asset‑level hazard exposures and impact metrics (e.g., heat stress, flood, wind) for current and future horizons (e.g., 2030/2050) under multiple scenario pathways.
  • Computes risk scores and identifies top drivers (hazards, time horizons, locations).
  • Generates prioritized adaptation recommendations (e.g., cooling upgrades, floodproofing) and, where possible, a simple cost/benefit or risk‑reduction estimate.
  • Presents results in a clear interactive UI or notebook report (maps, tables, charts).



  • Minimum deliverables:

  • Reproducible code/notebook + short README
  • Example inputs (addresses/assets or public open‑data samples)
  • A 5‑minute demo



  • Stretch ideas:

  • “Risk‑to‑Action” explanation: natural‑language justifications for each recommendation
  • Simple ROI calculator comparing adaptation options
  • Batch mode for many assets (CSV of addresses)

Portfolio Climate Risk Insights for Canadian Equities

Goal: Build an analytics workflow that turns company + asset‑level data into portfolio‑level climate risk insights and scenario narratives.


Build a prototype that:

  • Retrieves company and associated asset metrics
  • Aggregates to portfolio views (by sector, geography, hazard, horizon)
  • Highlights concentration of risk and what‑if scenarios (e.g., heatwave frequency increases; fluvial flood risk intensifies)
  • Surfaces Top‑N drivers and actionable tilts (e.g., supplier diversification, facility adaptation priorities)
  • Optionally exposes a natural‑language question interface (e.g., “Which holdings drive flood risk in 2035?”)



  • Minimum deliverables:

  • Reproducible code/notebook + short README
  • Example portfolio (ticker list or fabricated sample)
  • A 5‑minute demo



  • Stretch ideas:

  • Interactive dashboard with filters (hazard, horizon, sector)
  • Report generator (PDF/HTML) for investor or sustainability audiences

Judging Criteria

Correctness & clarity of methods/assumptions

Impact & usefulness for real stakeholders

Effective use of RiskThinking.ai data/APIs

Technical execution & design (reproducibility, UX)

Storytelling (compelling demo and insights)

CDTexpress Interface Dashboard