AI-powered disruption alerts for proactive supply chain management.
Enterprise teams lack real-time tracking and visibility in global supply chains, causing constant surprises and stockouts.
SupplyShield uses AI to predict and alert on risks like weather, strikes, or port delays from global data sources. Teams get risk scores, mitigation suggestions, and automated contingency planning. Prevent stockouts by acting before issues hit.
Enterprise teams managing global supply chains
Predictive AI from public + proprietary data, not just reactive tracking.
supportive
Overview of all supply chain risks with heatmaps.
Proactive notifications with probability scores.
Forecast delays using news, weather APIs.
Suggested reroutes or backups.
Assign scores to suppliers/routes.
Review past predictions accuracy.
What-if analysis for disruptions.
Embed risk scores in ERP.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| name | text | No |
| created_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| organization_id | uuid | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| name | text | No |
| risk_score | int | Yes |
| organization_id | uuid | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| supplier_id | uuid | No |
| risk_type | text | No |
| probability | int | No |
| sent_at | timestamp | No |
Relationships:
/api/suppliersAdd supplier for monitoring
/api/risksFetch current risks
/api/alertsList alerts
No predictions
Email alerts only
None
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 80 | 4% | $134 | $1,608 |
| Month 6 | 500 | 9% | $1,785 | $21,420 |
AI alerts before problems hit your inventory.
Post in supply chain Reddit/Twitter polls on disruptions, DM respondents. Offer free audits of their suppliers. Network on LinkedIn with 'disruption prediction beta' posts.
Deep supplier audits
Slow, expensive
Real-time AI, self-serve
Improving AI model with user-submitted disruption data.
Geopolitical tensions and climate events increasing disruptions; LLMs enable affordable prediction.
AI prediction accuracy
Start with rule-based, iterate with data
Skepticism on AI
Transparency on sources and backtests
Success: 80% interested in tool
Success: Alert click rate >70%
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