Shelf-Level Execution Is a Continuous Signal
Compliance, planogram fit, and out-of-stock detection across thousands of stores - scored hourly and routed to field teams in the same day, not the next audit cycle.
From Shelf to Supply Chain
Transform merchandising, retail execution, demand forecasting, supply chains, and customer engagement with operational-grade AI systems built for modern CPG enterprises.
Four operational realities define how modern CPG enterprises run. Each is solvable today with operational-grade AI - not roadmap, not pilot.
Compliance, planogram fit, and out-of-stock detection across thousands of stores - scored hourly and routed to field teams in the same day, not the next audit cycle.
Replace monthly reporting with weekly signal-driven planning. Forecast SKU-level demand shifts six weeks ahead of inventory cycles - anchored to point-of-sale, not legacy assumption.
Brief to live, end-to-end, through one orchestration layer. Targeting, asset assembly, and channel deployment run as a single workflow - measured by time-to-market, not effort.
Raw material price forecasting, supplier risk scoring, and inventory rebalancing - built to detect disruption signals and reroute before the cost shows up on the P&L.
“Affine builds the operational AI layer that turns siloed CPG commercial functions into one continuously-running, measurable production system.”
“Every inch of shelf space optimized, compliant, and revenue-ready.”
Computer-vision retail execution platform optimizing shelf layouts, merchandising compliance, and in-store inventory visibility.
SKU-level demand forecasting models - feeding market potential assessment and rolling financial planning across a global brewer’s portfolio.
Assortment engine using demand transference modeling - replaces low-performing SKUs with higher-yield alternatives at the planogram level.
Deep-learning computer vision pipeline automating production-line defect detection for fem-care SKUs in near real time.
Conjoint-analytics scenario engine for pricing strategy, portfolio mix, and cannibalization simulation across the active SKU portfolio.
Centralized ML engine forecasting raw material procurement costs for a global food & beverage enterprise.
Computer-vision pipeline monitoring shelf organization and inventory visibility across the in-store estate, in near real time.
Affine builds operational-grade AI for CPG across merchandising, retail execution, demand forecasting, supply chains and customer engagement. That includes shelf-level compliance scored continuously, SKU-level forecasting at weekly granularity and campaigns that go from brief to live in days. For a global brewer, Affine's SKU-level demand forecasting improved forecasting accuracy to about 95%.
Affine's CPG deployments include demand forecasting that reached about 95% accuracy for a global brewer, SKU rationalization that improved sales volume by 5–10%, machine vision that achieved about 99% defect detection accuracy on a production line, and conjoint-based price optimization that increased overall market share by about 4%.
Affine's CPG agents are Shelf Intelligence for shelf space and compliance, the Quin Agent for business answers without SQL, the Retail End Cap Design Agent, the Campaign Management Agent, the Forecast Intelligence Platform for demand forecasts without waiting on the data science queue, and the Quality Assurance and Defect Detection Agent for catching defects on the line.
Affine's Shelf Intelligence is a computer-vision retail execution platform that optimizes shelf layouts, merchandising compliance and in-store inventory visibility. It generates demand-driven planograms from sales intelligence, allocates space and inventory capacity, and tracks visual compliance with real-time execution reporting. Affine's in-store analytics deployments have improved store-level inventory visibility and on-shelf product availability.
From retail execution and predictive forecasting to AI-powered merchandising and autonomous campaign management, Affine helps CPG enterprises unlock measurable business impact through operational-grade AI systems.