ShelfCast is an AI agent that continuously forecasts retail demand at the SKU level, optimizes inventory, and delivers the analysis that consulting firms charge $500/hr for.
Retailers hire IBM, Deloitte, or McKinsey to analyze demand patterns. Six-month engagements. The insights are outdated by the time the final deck ships.
Blue Yonder and o9 Solutions require massive data integration projects, dedicated IT teams, and budgets that only Fortune 500 retailers can justify.
Most mid-market retailers still forecast with Excel. They miss seasonal shifts, ignore external signals, and react to stockouts instead of preventing them.
Newer tools like Prediko only work for online DTC brands. Retailers with physical stores and multiple channels have no affordable option.
Plug in your POS system, ERP, or upload CSV exports. ShelfCast ingests historical sales, promotions, seasonal patterns, and external signals like weather and local events.
Machine learning models map demand patterns at the SKU and store level. The agent identifies what drives your sales, not just what happened last year.
Every day, ShelfCast generates updated demand predictions, flags stockout risks, recommends reorder quantities, and reports what changed and why.
| Enterprise tools | ShelfCast | |
|---|---|---|
| Implementation time | 6-18 months | Days |
| Annual cost | $200K-$5M+ | Fraction of that |
| Data requirements | 2+ years of ERP data | Any sales history |
| Consulting required | Dedicated team | None. AI runs autonomously |
| Forecast frequency | Weekly or monthly batches | Daily, continuous |
| Channel support | Often siloed | Unified: in-store + online |
ShelfCast is building the future where demand intelligence runs continuously, autonomously, and affordably for every retailer, not just the Fortune 500.