AI-driven anomaly detection to prevent grid failures before they happen.
Enterprise teams in energytech lack scalable software for real-time grid monitoring that integrates seamlessly with legacy infrastructure, causing frequent downtime.
VoltSentinel ingests legacy grid data via simple APIs and uses ML to detect subtle anomalies like voltage spikes or load imbalances. It integrates with existing SCADA without hardware changes, sending predictive alerts to slash downtime. Teams collaborate on unified dashboards with drill-down analytics.
Enterprise teams in energytech managing grid operations
Out-of-box ML models fine-tuned on energy datasets, accurate 95% on day one.
professional
ML scans for deviations in voltage/current patterns.
Forecast issues 30-60min ahead via SMS/push.
Heatmaps and trends from multiple legacy sources.
RESTful API endpoints for easy legacy push.
Auto-escalate unresolved issues to managers.
Weekly automated summaries emailed.
Upload data to retrain models.
Post alerts to channels.
Phone calls for critical events.
Test scenarios without live data.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| name | text | No |
| tier | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| org_id | uuid | No |
| name | text | No |
| api_key | text | No |
| active | bool | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| source_id | uuid | No |
| type | text | No |
| confidence | int | No |
| resolved | bool | No |
| detected_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| source_id | uuid | No |
| metric_value | int | No |
| timestamp | timestamp | No |
Relationships:
/api/sourcesAdd data source
/api/readingsIngest legacy data
/api/anomaliesList recent anomalies
/api/anomalies/:id/resolveMark as resolved
/api/dashboardAnalytics data
/api/reportsFetch trend reports
/api/alerts/prefsUpdate notification settings
1000 readings/mo
10 team alerts/day
None
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 25 | 4% | $45 | $540 |
| Month 6 | 120 | 12% | $720 | $8,640 |
Legacy data meets modern ML for proactive energy ops.
Post in energy Discord/Forums offering free AI audits of sample data. Target mid-size utilities via LinkedIn sales navigator with 'free anomaly scan' hook. Partner with SCADA consultants for referrals.
Full grid control
No easy AI, heavy install
API-first AI at SaaS pricing
Fine-tuned ML models improving with aggregated anomaly data.
AI maturity + rising cyber/physical grid threats demand predictive tools.
ML false positives
Threshold tuning + user feedback
AI skepticism in energy
Free trials with proven accuracy
Success: 80% interested
Success: 3 paid betas
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