Forecasting tools can become another heavy implementation with consultants, configuration, and training.
Forecast exceptions, not another ERP
Know which SKUs need a planner’s attention today.
Turn a stable inventory export into explainable reorder, stockout, overstock, and data-quality exceptions—without pretending the forecast replaces judgment.

Why this exists
Built around the work competitors leave behind.
SMB manufacturers and distributors managing multi-location inventory in an ERP or spreadsheets.
Baseline forecasts miss SKU context such as promotions, supply disruptions, and distorted demand after stockouts.
Teams spend hours reconciling data before they can decide what to buy.
The focused promise
A daily or weekly exception digest explaining demand, lead-time, stockout, and data-quality drivers.
We deliberately keep judgment, authorization, and consequential decisions with your team. The pilot automates the legwork that can be made observable and repeatable.
- Explainable exceptions with the inputs and rule that triggered them
- Separate source-data quality warnings from genuine planning risk
- Human-approved reorder decisions with a complete audit trail
Fast path to evidence
Useful before it becomes software.
One bounded workflow. Real output. A clear go/no-go decision.
- 1Step 1
Map one standard export for SKU, location, sales, stock, open POs, and lead time.
- 2Step 2
Backtest exceptions against one historical period with a planner.
- 3Step 3
Run a supervised live digest without writing purchase orders.
Hard boundary: No autonomous purchasing, stockout or savings guarantee, ERP write, supplier commitment, or replacement for a qualified inventory planner.
Competitor-review intelligence
Recurring friction became product requirements.
We reviewed dated public operator discussions, preserved the caveats, and converted the repeated pain into design choices. No scraped review-marketplace content and no invented testimonials.
Cin7 · Brightpearl · Inventory Planner · Odoo
An operator evaluating many inventory systems found several capable options too ERP-like, expensive, and implementation-heavy for a smaller team.
Our response: Stay an export-based exception overlay with no migration, no master-data ownership, and a bounded first mapping.
See evidence and caveatCin7 ForesightAI · Netstock · Spreadsheet forecasting
The discussion distinguished baseline forecasts from SKU-level judgment around campaigns and disruptions and raised pricing and add-on concerns.
Our response: Explain every exception, expose source inputs, and require planner confirmation instead of presenting a single opaque forecast as truth.
See evidence and caveatSpreadsheet planning · Inventory-planning software
An experienced ecommerce operator described reorder timing, quantity, lead times, minimums, and demand spikes as persistent judgment-heavy problems even with sales data.
Our response: Market fewer surprises and an attention queue—not perfect prediction or autonomous purchasing.
See evidence and caveatReciprocity, with something genuinely useful
Take the checklist, even if we never work together.
The inventory forecast readiness checklist is a practical starting point for improving this workflow today.
Download free CSV- 01Separate observed demand from stockout-distorted demand
- 02Track actual and expected supplier lead time
- 03Flag promotions, new items, bundles, and missing history
- 04Require a planner to confirm every purchase decision
Design-partner offer
Forecast Exception Proof Run
€499 for one location and export
Expected plan: from €199/month. Future pricing is a hypothesis, not a payment commitment.
- Explainable exceptions with the inputs and rule that triggered them
- Separate source-data quality warnings from genuine planning risk
- Human-approved reorder decisions with a complete audit trail
- Direct access to the small Venthry team
Plain-English risk reversalNo connector or ERP migration. If the fixed export cannot support explainable exceptions, the pilot stops before live use.
Small first commitment
See if the pilot fits.
Reserve a nonbinding fit review. No card, operational files, credentials, or customer data belong in this form. We reply personally with the next safe step.
Questions, answered plainly
No hidden implementation story.
Does AI place purchase orders?+
No. The validation product is a read-only exception layer; planners retain purchasing authority.
Do we need to replace our ERP?+
No. The first test starts with a stable, standardized export.
Can it forecast new products?+
Sparse-history and new-item cases are explicitly flagged for human judgment rather than given false precision.
How do you test accuracy?+
The pilot backtests whether the selected rules would have surfaced useful decisions and records false positives.