VoltSight

AI-driven anomaly detection for multi-site energy grids.

Score: 7.7/10CanadaMedium BuildReady to Spawn
Brand Colors

The Opportunity

Problem

Energytech teams cannot achieve real-time oversight of distributed grid assets because IoT platforms lack multi-site deployment support.

Solution

VoltSight uses AI to detect anomalies in real-time across distributed grid assets, alerting teams before issues escalate. It supports multi-site deployments by normalizing data from various IoT sources. Teams gain predictive insights without rebuilding their infrastructure.

Target Audience

Energytech teams managing distributed enterprise grid assets across multiple sites

Differentiator

Out-of-box AI models tuned for grid-specific anomalies like voltage spikes.

Brand Voice

professional

Features

Anomaly Detection

must-have30h

ML-based detection of outliers in metrics across sites.

Smart Alerts

must-have20h

Prioritized notifications with root cause suggestions.

Multi-Site Aggregation

must-have18h

Federate data from all sites for global anomaly views.

Alert History

must-have15h

Log and analyze past incidents.

Integration Wizard

must-have12h

Easy connect to IoT platforms.

Predictive Maintenance

nice-to-have20h

Forecast potential failures.

Slack/Teams Integration

nice-to-have10h

Channel notifications.

Custom ML Models

nice-to-have15h

User-trained models.

Total Build Time: 140 hours

Database Schema

organizations

ColumnTypeNullable
iduuidNo
nametextNo
created_attimestampNo

Relationships:

  • users.org_id -> organizations.id

sites

ColumnTypeNullable
iduuidNo
org_iduuidNo
nametextNo

Relationships:

  • org_id -> organizations.id

anomalies

ColumnTypeNullable
iduuidNo
site_iduuidNo
scorefloatNo
resolvedboolNo
timestamptimestampNo

Relationships:

  • site_id -> sites.id

baselines

ColumnTypeNullable
iduuidNo
site_iduuidNo
metric_typetextNo
thresholdfloatNo

Relationships:

  • site_id -> sites.id

API Endpoints

GET
/api/sites

List sites

🔒 Auth Required
GET
/api/anomalies

Fetch recent anomalies

🔒 Auth Required
PUT
/api/anomalies/:id/resolve

Mark as resolved

🔒 Auth Required
POST
/api/webhook/data

Ingest IoT data for AI

POST
/api/baselines

Update thresholds

🔒 Auth Required

Tech Stack

Frontend
Next.js 14 + Tailwind + Framer Motion
Backend
Next.js + Supabase
Database
Supabase Postgres
Auth
Supabase Auth
Payments
Stripe
Hosting
Vercel
Additional Tools
Vercel AI SDK for anomaliesSupabase Vector for ML

Build Timeline

Week 1: Auth and sites

35h
  • Auth
  • Site CRUD
  • Data ingestion

Week 2: AI core

45h
  • Anomaly detection logic
  • Baselines

Week 3: Alerts UI

40h
  • Alert dashboard
  • Notifications

Week 4: Integrations

30h
  • Payments
  • RBAC

Week 5: Polish

25h
  • History views
  • Nice-to-haves

Week 6: Launch prep

20h
  • Tests
  • Landing
Total Timeline: 6 weeks • 195 hours

Pricing Tiers

Free

$0/mo

50 anomalies/mo

  • 1 site
  • Basic AI alerts

Pro

$30/mo

500 anomalies/mo

  • Unlimited sites
  • Smart alerts
  • Integrations

Enterprise

$99/mo

Unlimited

  • All + Custom AI
  • API access

Revenue Projections

MonthUsersConversionMRRARR
Month 1804%$96$1,152
Month 67007%$1,470$17,640

Unit Economics

$90
CAC
$450
LTV
5%
Churn
85%
Margin
LTV:CAC Ratio: 5.0xExcellent!

Landing Page Copy

Catch Grid Anomalies Before They Fail

AI-powered multi-site detection for energy assets.

Feature Highlights

Instant anomaly spotting
Cross-site insights
Predictive alerts
Easy setup
Team notifications

Social Proof (Placeholders)

"'Saved us downtime' - Utility Ops"
"'AI that understands grids' - Tech Lead"

First Three Customers

Target 'IoT energy' keywords on LinkedIn, offer free AI audits. Share anomaly detection demo on Energy Central forums. DM attendees from DER conferences.

Launch Channels

Product HuntHacker Newsr/energyLinkedInIndie Hackers

SEO Keywords

grid anomaly detectionAI energy grid monitoringmulti-site IoT alertspredictive grid maintenance

Competitive Analysis

Freemium
Strength

Visual IoT

Weakness

No built-in AI for grids

Our Advantage

Grid-tuned AI

🏰 Moat Strategy

Anonymized anomaly data moat for improving ML models.

⏰ Why Now?

AI maturity + rising DER failures due to decentralization.

Risks & Mitigation

technicalhigh severity

ML false positives

Mitigation

User feedback loops

legalmedium severity

Data privacy regs

Mitigation

SOC2 compliance path

Validation Roadmap

pre-build5 days

Survey 15 grid managers

Success: 80% validate AI need

mvp10 days

Demo video signups

Success: 20 waitlist

Pivot Options

  • General anomaly detection SaaS
  • Focus on wind farms
  • Pure alerting without AI

Quick Stats

Build Time
195h
Target MRR (6 mo)
$1,500
Market Size
$1800.0M
Features
8
Database Tables
4
API Endpoints
5