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Retail
Demand forecasting
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Production-Ready AI Solution
Retail · Enterprise Solution

Demand forecasting

SKU/store forecasts that actually beat the baseline.

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LIVE AI ENGINE
Real-Time Execution Pipeline

Demand forecasting · Live Event Stream

STREAMING
STAGE 01INGEST
Enterprise Data
Lakehouse & APIs
STAGE 02ACTIVE
Breww AI Kernel
Multi-Agent Engine
STAGE 03ACTION
Automated Action
Low Latency SLA
EVENT MONITOR · RETAIL
ONLINE

[INGEST] Multi-source telemetry batch synced (2,480 items)

p99: 12.4ms
Throughput: 420 ev/s
ZERO-DRIFT SLA
The problem

What we hear

Legacy forecasts miss on new products, promos, and seasonality — inventory pays the price.

Our approach

How we solve it

Hierarchical demand models with promo and macro features, reconciled top-down and bottom-up.

Outcomes

Measured impact

  • Lower forecast error at the SKU/store level
  • Fewer stock-outs and markdowns
  • Better vendor collaboration

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Store performance

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Out-of-stock prediction

Prevent lost sales at the shelf.

Talk to us

Bring demand forecasting into production.

Share a couple of lines about your setup — a senior partner will get back within a business day.

Discuss this use case

Tell us about your organization and what problem you are solving.

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Demand forecasting — Retail · DataCaffe.ai