Enhancing Route-to-Market Strategies for CPG Companies with Advanced Computer Vision & AI/ML Solutions

Industry

Retail

Engagement

Oct 22 - present

Accuracy

97%+

Recognizing FMCG Products and their parameters

Ivy Mobility is a leading provider of intelligent Route-to-Market (iRTM) solutions for the Consumer Packaged Goods (CPG) industry, focusing on automation, productivity, and sales growth. Since 2017, Ivy Mobility has partnered with SoluteLabs on multiple initiatives to drive innovation and efficiency.

In this initiative, we collaborated to develop a sophisticated end-to-end Computer Vision pipeline, incorporating advanced technologies such as Object Detection, Image Classification, and Optical Character Recognition (OCR).

Services

AI/ML Development

MLOps

Python Development

Prasaanth Subbiah

Director of Strategy, IvyMobility

It was a very, very fruitful engagement because we were successfully able to roll out the product, as in any product organization time-to-market is more important, and that's where SoluteLabs helped us so we were able to build that mobile solution in a record time and roll it out for the customers.

Prasaanth Subbiah

Director of Strategy

Problem Statement

The client wanted Fieldforce agents who use their app track products on shelves by capturing images, and process it on the cloud to extract various parameters such as placement, availability, price tracking and more. This would also enable syncing data for supervisor action, improving their efficiency and accuracy

Outcome

Ivy Eye is an Android & IOS application enabling merchandisers to track products on shelves using their mobile devices and sync data for supervisor action.

Point of Sales Materials (POSM)

Display Tracking

Assortment Tracking

Price Monitoring

Promotion Tracking

IvyEye Image Recognition

Ivy Eye is an Android & IOS application enabling merchandisers to track products on shelves using their mobile devices and sync data for supervisor action.

Display Tracking

Accurately identify and track FMCG products on retail shelves, enabling real-time KPI calculation and faster decision-making for Ivy Mobility’s customers

Assortment Tracking

Identify and count SKUs on shelves, tracks competitor products, and monitors shelf placement, ensuring optimal product availability and competitive analysis.

Price Tracking

Detect and read price tags on shelves, accurately capturing pricing information for each SKU to ensure accurate price monitoring and compliance with promotional pricing strategies

Promotion Tracking

Identify and categorize promotional tags on products, ensuring accurate tracking and execution of promotional activities and pricing strategies.

AI Tech Stack

The Ivy Eye project leverages a sophisticated AI tech stack, utilizing advanced frameworks and models to deliver high-accuracy object detection, image classification, and OCR capabilities.

ML Frameworks

We utilized TensorFlow and PyTorch for building and training deep learning models. These frameworks provided robust libraries and tools for developing and fine-tuning our neural networks, ensuring optimal performance in object detection and image classification tasks.

AI Models

The project utilizes specialized AI models, either pre-trained for relevant tasks like object detection and image classification, or custom-built for specific needs. These models are fine-tuned with Ivy Eye's data to achieve high accuracy in identifying and classifying products on shelves captured through mobile device cameras.

MLOps

To streamline the deployment and maintenance of our AI models, we adopted MLOps practices. This included using Docker for containerization, Kubernetes for orchestration, and CI/CD pipelines for automated testing and deployment. These practices ensured efficient model updates, scalability, and reliability of the AI components within the Ivy Eye application.

Anand Venkatesan

Head of Strategic Initiatives, IvyMobility

We used to have SoluteLabs as a part of our discovery sessions, and for key design sessions, and deliver that with perfection. And they used to be agile in working. So we had no problems in ensuring that the work that we plan for, the team gets it completed on time. So there is always a good communication rhythm that happens, and there is a good positive mindset in imbibing this whole agile base of development.