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https://store-images.s-microsoft.com/image/apps.56602.9b0d9940-a519-47fb-a76a-9b62ebd813eb.1d3e10ea-7e56-4231-9242-6e03057975a1.9d38541e-82b4-4907-bb71-6fe5cf00c7ec

Market AI : 8 Weeks Proof of Concept

LTIMindtree Limited

Introduction

Azure Open AI powered intelligent market share solution for SKU shelf share compliance and occupancy analytics. It is a customizable solution to identify and calculate the share of the target brand’s SKUs visibility on the shelf in a store against the competition.

An Azure Open AI powered Brand and Market Share Analytics Solution for Consumer Product Goods

Key platform features

Plug and Play solution to accelerate your vision-based market analysis needs at every store which brings off-the-shelf features like –

• Reusable feature store
• Reusable data models
• Prebuilt algorithms
• Scalable MLOps and APIs
• Narrative, storytelling, and visualizations
• Threshold-based escalations
• Prescriptive actionable alerts and auto reminders
• Role-based access control

Platform Highlights

Provides high performance and it is an easily deployable platform that enables the following.

• Effort - 80% reduction in time in terms of customization
• Accuracy – 85% baseline accuracy for all models
• Resource – Start generating immediate value with 75% fewer data science resources.
• Feedback – In-built feedback loop for automated re-training of models
• Architecture – Multi-input deep learning model helps reduce the number of models in production by 95% thus decreasing infra cost by 40%
• Latency - Kubernetes-based deployment for reduced latency

At a glance

https://store-images.s-microsoft.com/image/apps.41980.9b0d9940-a519-47fb-a76a-9b62ebd813eb.1d3e10ea-7e56-4231-9242-6e03057975a1.66bcfa4e-cdad-467d-94f0-cf23512f143a
https://store-images.s-microsoft.com/image/apps.11861.9b0d9940-a519-47fb-a76a-9b62ebd813eb.1d3e10ea-7e56-4231-9242-6e03057975a1.509904c2-24c9-4745-8d2a-202ba02ffa66
https://store-images.s-microsoft.com/image/apps.7076.9b0d9940-a519-47fb-a76a-9b62ebd813eb.1d3e10ea-7e56-4231-9242-6e03057975a1.c23417b8-760b-44fa-8d7a-c2320b4acdfd
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