How accurate is the forecast?

Stores with 18+ months of clean historical data typically see 70 to 85 percent SKU-level accuracy at the weekly forecast horizon. Daily forecasts are noisier; monthly forecasts are tighter. Realistic accuracy depends on your category.

What about new product launches?

New SKUs without history use category-level priors and refine quickly. We surface the uncertainty band in the forecast so your inventory team knows where the model is confident and where it is guessing.

Does it integrate with our ERP?

Yes. We integrate with NetSuite, Microsoft Dynamics, SAP, Odoo and custom ERPs via API. Forecasts and reorder triggers push to the ERP for human review or auto-execution depending on your governance.

Will it handle promotions?

Yes if marketing spend and promotional calendar data is shared. Promotional lift is hard to forecast without spend signals; we ask for them as part of training data.

Can your team override the forecast?

Yes. Every forecast has a human-override input in the dashboard. The model logs the override for future training. Major demand disruptions need humans, and we design for that.

AI Automation for Ecommerce

KI-Bestandsprognose

KI-Bestandsprognose. Nachfrageprognose, Nachbestellauslöser, Erkennung von langsamen Verkäufen, Integration mit ERP und WMS.

Timeline: 6 to 10 weeks
Forecast: Per-SKU
Triggers: Automated reorder
Measurement: Accuracy delta

Overview

What it is.

KI-gesteuerte Bestandsprognose für E-Commerce-Shops. Nachfrageprognose basierend auf historischen Verkaufszahlen, saisonalen Mustern und Marketingausgaben. Automatisierte Nachbestellauslöser, Erkennung von langsamen Verkäufen und Integration mit Ihrem ERP, WMS oder 3PL. Die meisten Projekte werden in 6 bis 10 Wochen geliefert. Die Prognosegenauigkeit wird gegen eine Basislinie gemessen; signifikante Verbesserungen in den ersten 90 Tagen, während das Modell Ihre spezifischen Nachfrage Muster lernt.

What you get

Deliverables.

Forecasting model trained on your historical sales
Seasonal pattern detection per SKU
Reorder trigger configuration
Slow-mover detection with markdown recommendations
Integration with your ERP, WMS or 3PL
Dashboard for stock managers
Forecast accuracy reporting
Operations runbook for your inventory team

Honest limits

What it isn't.

Forecast quality improves with 18+ months of historical data
New SKUs without history use category-level priors and improve over time
Major disruption events (pandemic, war, supply chain shocks) need human override

Not sure if it's a fit? Email us. We'll tell you straight.

How it works

From inquiry to handover.

01
1. Discovery
Audit existing inventory data. Confirm ERP and WMS integrations.
02
2. Foundation
Historical data ingested. Initial forecasting model trained.
03
3. Build
Reorder triggers, slow-mover detection, integrations wired up.
04
4. Launch + measurement
Soft launch with shadow forecasting alongside existing process. 90-day accuracy delta reported.

Frequently asked

Questions we get from people about to book.

How accurate is the forecast?: Stores with 18+ months of clean historical data typically see 70 to 85 percent SKU-level accuracy at the weekly forecast horizon. Daily forecasts are noisier; monthly forecasts are tighter. Realistic accuracy depends on your category.
What about new product launches?: New SKUs without history use category-level priors and refine quickly. We surface the uncertainty band in the forecast so your inventory team knows where the model is confident and where it is guessing.
Does it integrate with our ERP?: Yes. We integrate with NetSuite, Microsoft Dynamics, SAP, Odoo and custom ERPs via API. Forecasts and reorder triggers push to the ERP for human review or auto-execution depending on your governance.
Will it handle promotions?: Yes if marketing spend and promotional calendar data is shared. Promotional lift is hard to forecast without spend signals; we ask for them as part of training data.
Can your team override the forecast?: Yes. Every forecast has a human-override input in the dashboard. The model logs the override for future training. Major demand disruptions need humans, and we design for that.

Ready to start?

Tell us about your project.

A member of our team reads every message. Replies within one business day. No sales call required.

See all services

AI Automation for Ecommerce

KI-Bestandsprognose

KI-Bestandsprognose. Nachfrageprognose, Nachbestellauslöser, Erkennung von langsamen Verkäufen, Integration mit ERP und WMS.

Timeline: 6 to 10 weeks
Forecast: Per-SKU
Triggers: Automated reorder
Measurement: Accuracy delta

Overview

What it is.

What you get

Deliverables.

Forecasting model trained on your historical sales
Seasonal pattern detection per SKU
Reorder trigger configuration
Slow-mover detection with markdown recommendations
Integration with your ERP, WMS or 3PL
Dashboard for stock managers
Forecast accuracy reporting
Operations runbook for your inventory team

Honest limits

What it isn't.

Forecast quality improves with 18+ months of historical data
New SKUs without history use category-level priors and improve over time
Major disruption events (pandemic, war, supply chain shocks) need human override

Not sure if it's a fit? Email us. We'll tell you straight.

How it works

From inquiry to handover.

01
1. Discovery
Audit existing inventory data. Confirm ERP and WMS integrations.
02
2. Foundation
Historical data ingested. Initial forecasting model trained.
03
3. Build
Reorder triggers, slow-mover detection, integrations wired up.
04
4. Launch + measurement
Soft launch with shadow forecasting alongside existing process. 90-day accuracy delta reported.

Frequently asked

Questions we get from people about to book.

How accurate is the forecast?: Stores with 18+ months of clean historical data typically see 70 to 85 percent SKU-level accuracy at the weekly forecast horizon. Daily forecasts are noisier; monthly forecasts are tighter. Realistic accuracy depends on your category.
What about new product launches?: New SKUs without history use category-level priors and refine quickly. We surface the uncertainty band in the forecast so your inventory team knows where the model is confident and where it is guessing.
Does it integrate with our ERP?: Yes. We integrate with NetSuite, Microsoft Dynamics, SAP, Odoo and custom ERPs via API. Forecasts and reorder triggers push to the ERP for human review or auto-execution depending on your governance.
Will it handle promotions?: Yes if marketing spend and promotional calendar data is shared. Promotional lift is hard to forecast without spend signals; we ask for them as part of training data.
Can your team override the forecast?: Yes. Every forecast has a human-override input in the dashboard. The model logs the override for future training. Major demand disruptions need humans, and we design for that.

Ready to start?

Tell us about your project.

A member of our team reads every message. Replies within one business day. No sales call required.

See all services

KI-Bestandsprognose

What it is.

Deliverables.

What it isn't.

From inquiry to handover.

1. Discovery

2. Foundation

3. Build

4. Launch + measurement

Questions we get from people about to book.

Tell us about your project.

KI-Bestandsprognose

What it is.

Deliverables.

What it isn't.

From inquiry to handover.

1. Discovery

2. Foundation

3. Build

4. Launch + measurement

Questions we get from people about to book.

Tell us about your project.