COMPARISON
Most retail brands hit a wall when it comes to manually forecasting demand and inventory management.
Our AI agents help automate these critical processes, enabling retail brands to scale across multiple brands without hiring.
Trusted by the best
Data usually lives in silos, for example, sales data in NetSuite, marketing spends in Snowflake, international sales scattered across journal entries with no SKU-level detail.
Teams spend hours every month manually pulling data together for analysis. Because there's no other way to see the full picture.
Manual data entry mistakes create discrepancies between system records and actual stock levels.
With manual forecasting, retailers often miss cannibalization analysis, pricing elasticity, marketing spend ROI by SKU, seasonal pattern detection, and more.
Connect different platforms, including NetSuite, Snowflake, Looker, and SharePoint, in minutes.
Generate forecasts for thousands of SKUs in under 10 minutes. Results match your existing Excel template format.
Adopt AI automatically pulls transaction-level sales data, marketing spend by channel, and historical promotional calendars. No more monthly exports required.
AI agents flag anomalies like sudden demand spikes or inventory mismatches for human review before executing high-stakes decisions like expediting large purchase orders.
A 16-step pipeline handles data processing, pattern detection, and forecast generation with confidence scores. Six forecasting models run simultaneously.
Snowflake API pulls daily spend by channel, brand, and region with history for seasonal patterns. Looker handles legacy programmatic data while SharePoint imports promotional calendars.
Connect with your existing tech stack within minutes!
PLATFORMS WE CONNECT WITH
NetSuite
CRM
Internal Apps
SharePoint
Looker
Snowflake
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When the platform isn't confident about a prediction, it flags it. The edge cases can be reviewed while the rest runs automatically.
Adopt AI was built for retail forecasting. Our platform understands SKU hierarchies, product families, cannibalization dynamics, promotional calendar inference from sales patterns, and seasonal patterns. It’s also pre-configured for NetSuite, Snowflake, and Looker.
Cloud-First
On-Premise
Hybrid
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Time Savings:
4-5 hours to 15 minutes
AI agents test multiple forecasting models simultaneously and select the best performer for each SKU. Improved demand predictions reduce stockouts during peak seasons and prevent overstock that ties up working capital.
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AI agents analyze cannibalization risk when launching new SKUs by modeling how similar products performed historically. This prevents revenue cannibalization and set optimal pricing from day one.
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Continuous monitoring flags stockout risk across hundreds of SKUs and automatically suggests rebalancing inventory between warehouses or expediting purchase orders.
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AI agents analyzes marketing channels (Meta, Search, Display), identifying saturation points where each dollar stops generating returns. Reallocate wasted spend to higher-performing channels without increasing total budget.
