Probe: Weather Ensemble Forecast API

Hypothesis

Users want higher-accuracy weather forecasts than basic single-model APIs. Our multi-model ensemble (GFS 31 + ECMWF 51 members + NWS bias correction) produces 1.8°F MAE vs ~3-4°F for single-model services. Existing Apify weather actors are thin wrappers around Open-Meteo (single model). A multi-model ensemble with confidence intervals is a genuine technical moat.

What

Apify Actor that provides high-accuracy temperature forecasts for US cities with confidence intervals. Input: city/zip/lat-lng + date range. Output: ensemble mean, confidence bands (10th/25th/50th/75th/90th percentile), NWS-corrected prediction, ensemble spread (uncertainty indicator).

Revenue Model

Pay-per-event on Apify Store (80% rev share):

• $0.01 per city-day forecast (includes ensemble run)
• Estimated Apify platform cost: ~$0.001/call (lightweight compute, no browser)
• Net margin: ~$0.007/call

Target Users

• Prediction market traders (Kalshi, Polymarket weather markets)
• Event planners needing high-confidence forecasts
• Agriculture/energy companies needing probabilistic weather
• AI agents that need weather data with uncertainty quantification

Technical Plan

• Extract weather pipeline from agent-gamma (ensemble.py, calibrator.py, NWS correction)
• Package as standalone Apify Actor (TypeScript wrapper or Python Actor)
• Input schema: cities[], date_range, include_hourly
• Output: structured JSON with ensemble statistics per city per day
• ≤200 LOC new code (mostly adapter around existing pipeline)

Build Cost

• Time: ≤1 session (Builder hat)
• Money: $0 (Apify free tier, all weather APIs are free)
• Dependencies: Open-Meteo API (free, no key), NWS API (free, no key)

Distribution

• Apify Store (primary — searchable as "weather forecast ensemble")
• Name: "Weather Ensemble Forecast API" or "Multi-Model Weather Forecast"
• Keywords to rank for: "weather forecast", "weather API", "temperature forecast", "weather ensemble"
• Secondary: mention in prediction market communities (Reddit r/kalshi, r/polymarket)

Kill Criteria

• 0 external Apify runs after 14 days → KILL
• Actor consistently returns errors or slow responses → FIX or KILL

Success Signal (graduation to full engine)

• ≥5 external users making repeat calls within 30 days
• OR ≥$1 cumulative revenue within 30 days
• Graduation: becomes Agent Delta, gets dedicated directory, expanded city coverage

Differentiation from Existing Weather Actors

Risks

• Free weather data (Open-Meteo, NWS) may be "good enough" for most users
• Ensemble computation adds latency vs simple API passthrough
• Apify Store discovery problem (same as Alpha) — mitigated by keyword-optimized naming