AI predicts and auto-optimizes solar output for your variable WFH days.
Solar panel app users cannot automate energy savings because apps lack integration with remote work calendars, forcing manual adjustments based on WFH schedules.
BeamOptimizer uses AI to analyze your calendar, weather forecasts, and historical solar data for proactive energy adjustments. It integrates with solar apps to preemptively set optimal export/import modes. Achieve max savings without ever checking the app manually.
Homeowners with solar panels who work remotely and have variable WFH schedules
ML models trained on anonymized user WFH patterns for hyper-accurate predictions.
professional
Forecast savings based on calendar + weather.
Pulls real-time forecasts to adjust solar strategies.
Daily pulls from Enphase/SolarEdge APIs.
Approve or auto-execute AI recommendations.
Improves predictions from your usage history.
Test 'what-if' WFH changes.
Prioritize Powerwall charge/discharge.
Family calendar aggregation.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| date | timestamp | No |
| output_kwh | int | No |
| weather_data | jsonb | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| predicted_date | timestamp | No |
| recommended_action | text | No |
| confidence | int | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| events | jsonb | Yes |
Relationships:
/api/predictGenerate daily predictions
/api/solar-dataIngest daily solar metrics
/api/apply-predictionExecute recommendation on solar API
/api/historyPast predictions and accuracy
7-day history
None
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 150 | 4% | $210 | $2,520 |
| Month 6 | 1,000 | 7% | $2,450 | $29,400 |
Predict WFH impacts on energy and auto-adjust for max savings.
Share AI demo video in r/solarpanels and r/remotework; Offer free Pro to top solar YouTubers' audiences; Cold email 50 Enphase users from public reviews.
Real-time data
No AI or calendar
Predictive intelligence
Energy disaggregation
Hardware req, no solar focus
Software-only AI for solar
User data moat for refining AI models faster than competitors.
AI accessibility + solar subsidies driving installs amid energy crisis.
AI accuracy low initially
Hybrid rules + ML, A/B test
AI API costs overrun
Self-hosted models post-MVP
Success: 80% would pay
Success: 70% accuracy validated
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