Eversight provides an AI‑driven platform that consolidates point‑of‑sale, inventory, competitor and consumer data to forecast demand elasticity, promotion lift, and optimal assortment. Its machine‑learning models generate pricing, discount and shelf‑space recommendations, which users can test through an interactive scenario‑planning dashboard and integrate via APIs into ERP and retail execution systems.
Funding
Funding not disclosed
Founders
Product
Problem
CPG manufacturers and retailers often rely on manual analysis of fragmented sales, inventory, and market data to set prices, plan promotions, and allocate shelf space. This process is time‑consuming, prone to error, and frequently results in suboptimal pricing, stockouts, and missed revenue opportunities.
Solution
Eversight offers an AI‑driven platform that aggregates point‑of‑sale, inventory, competitor, and consumer insights into a unified data lake. Advanced machine‑learning models estimate demand elasticity, promotional lift, and optimal assortment mix, generating data‑backed recommendations for pricing, promotion, and shelf allocation. Users can explore multiple “what‑if” scenarios through an interactive web dashboard, allowing rapid testing of price points, discount structures, and product placements. The platform refreshes forecasts in near real‑time, supporting dynamic adjustments to pricing and promotions as market conditions evolve. Seamless APIs connect the solution to ERP, retail execution, and analytics systems, automating data flow and reducing manual effort. By aligning commercial decisions with predictive consumer behavior, the system improves on‑shelf availability and captures incremental revenue.
Target Audience
The primary customers are CPG manufacturers, brand owners, and retail chains that manage pricing, promotional, and assortment decisions across their product portfolios.
Features
- Integrated data pipeline that ingests POS, inventory, competitor, and consumer datasets at scale
- Demand‑elasticity and price‑sensitivity models built on gradient‑boosted trees and deep learning
- Promotion‑lift forecasting engine that quantifies incremental sales and margin impact of discount strategies
- Assortment optimization module that recommends SKU mix and shelf space allocation per store tier
- Interactive scenario‑planning UI with drag‑and‑drop controls for rapid “what‑if” analysis
- RESTful APIs and pre‑built connectors for ERP, retail execution, and BI platforms
- Role‑based access controls and end‑to‑end encryption to meet industry data‑privacy standards