Real-Time Climate Resilience Scoring Engine with Vercel AI SDK
Insurers urgently need reactive climate risk dashboards that evaluate property-level exposure to compounding flood and wildfire hazards. You will build an interactive streaming risk assessment application using Vercel AI SDK to aggregate geospatial hazard maps and provide actionable resilience recommendations. Maintain a response streaming latency under 200ms with a risk calculation precision of 0.92.
What you are building
The core problem, expected build, and operating context for this challenge.
Build a streaming React/Next.js application powered by Vercel AI SDK to compute and stream property resilience scores.
How work is evaluated
Evaluate streaming UI latency and precision of climate resilience scoring recommendations.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
valid_score_range
Resilience score is an integer between 0 and 100.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
ttft_ms
Time To First Token latency in milliseconds • target: 200 • range: 0-500
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
recommendation_precision
Precision score of resilience hazard mitigations • target: 0.92 • range: 0-1
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Implement streaming AI UI interfaces using Vercel AI SDK (useChat, streamText)
Process geospatial flood and wildfire raster layers
Generate dynamic resilience modification recommendations
Optimize real-time model streaming latency in web runtimes
Reference links and supporting material
Geospatial flood risk maps, elevation grids, and property resilience upgrade catalogs.
Challenge setup
Evaluate streaming UI latency and precision of climate resilience scoring recommendations.
Challenge input
JSON address and coordinates
AI SDK
Lightweight TypeScript framework optimized for UI streaming and function tool calling.
Evaluated output
Streaming text payload and JSON resilience object
- Resilience score is an integer between 0 and 100.
- Time To First Token latency in milliseconds • target: 200 • range: 0-500
- Precision score of resilience hazard mitigations • target: 0.92 • range: 0-1
- Benchmark: GeospatialResilienceBench-2026
- Ttft Ms target: 200
- 1 public reference case
- JavaScript execution harness
- javascript sandbox (unavailable on Versalist)
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Vercel AI SDK · Required
- Alibaba · Optional
- Azure OpenAI Service · Optional
- Vercel AI SDK · Required
Evaluation contract
- valid_score_range · Weight 1
- ttft_ms · Weight 1
- recommendation_precision · Weight 1
Metrics
- ttft_ms · Target 200
- recommendation_precision · Target 0.92
Benchmarks
- GeospatialResilienceBench-2026
- general
Reference cases
- 1 public reference case
Workflow tasks
- Task 1
Input: JSON address and coordinates
Output: Streaming text payload and JSON resilience object
Execution harness: JavaScript
Evaluation tools
- AI SDK · Streaming Agent Framework
Recipe freeze marker
No recipe freeze time is recorded.