AI-powered discrepancy detection and auto-correction for omnichannel retail inventory.
Enterprise retail teams lose sales due to legacy POS systems failing to integrate omnichannel channels, resulting in inventory discrepancies.
InvDisrupt scans POS and e-com data for discrepancies using AI thresholds and auto-corrects minor issues like holdover stock. It learns from your operations to reduce false positives over time. Teams get proactive alerts before sales are lost.
Enterprise retail teams managing multi-channel sales operations
AI auto-resolution handles 80% of discrepancies without human input, unlike manual alert tools.
friendly
Daily scans across channels flagging mismatches.
Set rules for AI to adjust stock automatically.
Prioritized list of issues with one-click fixes.
Plug-and-play for major POS/ecom APIs.
Improves accuracy based on user feedback.
Per-SKU tolerance settings.
Assign issues to team members.
Charts of discrepancy patterns.
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| text | No | |
| created_at | timestamp | No |
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| channel | text | No |
| discrepancies_count | int | No |
| scanned_at | timestamp | No |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| scan_id | uuid | No |
| sku | text | No |
| delta | int | No |
| auto_fixed | bool | No |
| resolved_at | timestamp | Yes |
Relationships:
| Column | Type | Nullable |
|---|---|---|
| id | uuid | No |
| user_id | uuid | No |
| rule_name | text | No |
| threshold | int | No |
Relationships:
/api/scansTrigger manual scan
/api/discrepanciesList open discrepancies
/api/discrepancies/:id/fixResolve or auto-fix
/api/rulesCreate AI rule
/api/dashboardSummary stats
500 SKUs
5k SKUs
Unlimited
| Month | Users | Conversion | MRR | ARR |
|---|---|---|---|---|
| Month 1 | 40 | 4% | $40 | $480 |
| Month 6 | 180 | 12% | $360 | $4,320 |
InvDisrupt's AI auto-fixes 80% of issues instantly.
Run LinkedIn ads targeting 'retail operations manager'; Email 20 from retail job boards offering free audits; Join retail Discord/Slack for intros.
Inventory basics
No AI auto-fix
Proactive AI resolutions
Affordable
Manual discrepancy handling
Automation focus
Proprietary AI trained on user discrepancy data for superior accuracy.
Rise of AI tools makes auto-resolution feasible; retail hybrid sales surging.
AI false positives
User feedback loops
Enterprise data privacy fears
SOC2 compliance path
Success: 80% want auto-fix
Success: 50% auto-resolve rate
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