Pricing optimization

Noodoe built a generative AI advisor to optimize pricing strategies for EV charging stations by analyzing usage data and recommending pricing models.The solution was integrated into Noodoe's existing tech stack with Amazon Bedrock, Amazon EC2, and Amazon S3.

NoodoeEnergy & Utilities

Pattern built Content Brief on AWS to help ecommerce brands analyze keywords, search terms, product images, and customer reviews at scale.The solution uses Amazon Bedrock and Amazon Nova Foundation Models for high-volume data processing and prompt engineering, alongside Amazon S3, Amazon Textract, Amazon DynamoDB, Amazon ECS, and AWS PrivateLink.Pattern says the tool provides actionable insights from trillions of ecommerce data points to improve traffic and conversion.

PatternRetail

Majid Al Futtaim, the operator of Carrefour in the Middle East, implemented advanced data analytics and Microsoft Azure OpenAI Service to improve operational efficiency and deliver superior customer experiences. Their Enterprise Data Management initiative focused on digital transformation, automating pricing strategies, product placement, and routine data management.By combining proprietary tools ('Spider' and 'Geo'), Majid Al Futtaim optimized product pricing and placement using geospatial analysis. Teams now spend less time on routine tasks and more on value-adding activities, enabling proactive customer service and refined product offers. The use of Power BI enabled enhanced insights, while Azure Synapse supported robust analytics. Looking forward, the company is considering expanding its data governance using Microsoft Purview for master data management.The initiative yielded significant boosts in productivity, cost and efficiency optimization, and customer satisfaction. Majid Al Futtaim's approach is rooted in extracting business value from technology, prioritizing measurable outcomes and continuous feedback-driven improvement processes.

Majid Al FuttaimRetail

Blue Zinc Media, a UK-based digital marketing and lead generation agency, faced the challenge of efficiently managing massive pay-per-click (PPC) advertising accounts with a small team. Their objective was to meet strict cost-per-acquisition (CPA) targets across millions of keywords while maintaining the flexibility and performance clients demand. By partnering with Microsoft Advertising, Blue Zinc Media implemented an advanced Portfolio Bidding solution, enabling fully automated bid management. They relinquished manual controls and restrictions, granting the machine-learning-driven system unrestricted access for dynamic, outcome-based optimization. The result was a measurable increase in conversions (up 13%), maintained CPA within target, and successful scalability of the model for additional accounts, helping deliver sales growth for their clients.

Blue Zinc MediaProfessional Services

Yoho, Hong Kong's first online-to-offline ecommerce company, migrated its legacy database to Google Cloud SQL and modernized its backend to handle increased traffic and improve operational efficiency.The company integrated barcode scanning and point-of-sale systems with Cloud SQL and Compute Engine, enabling real-time inventory management and dynamic pricing.Yoho built an AI-powered pricing bot hosted on Compute Engine that monitors competitor prices and adjusts pricing dynamically across online and physical stores.They also use Google Cloud Translation API to offer multilingual support, improving customer engagement and accessibility.Yoho is exploring conversational AI chatbots with Contact Center AI and Dialogflow Enterprise Edition to enhance customer interaction and support.

YohoRetail

A global manufacturer of batteries and portable lighting products faced major disruptions to its shipping and supply chain during the COVID-19 pandemic. Previously, the company relied on manual, Excel-based processes that proved inadequate as prices spiked and lead times increased drastically. To address this, Protiviti partnered with the manufacturer to introduce advanced predictive analytics using Microsoft Azure, enabling rapid, accurate forecasting for 63 crucial shipping lanes. Data governance and cleansing methodologies were implemented, and hands-on training empowered the client's team to build, refine, and operationalize low-error predictive models. This data-driven transformation allowed the company to become highly agile in responding to market shifts, increase expense management accuracy, and become a pioneer in predictive analytics for the consumer goods shipping industry. The Azure-powered solution also laid the foundation for improved performance in related shipping and operations functions, permanently elevating the client's analytics capabilities.

GE Healthcare developed the GE Health Cloud on AWS to improve collaboration and access to medical imaging data, enabling faster and more secure sharing among clinicians globally.The solution collects, stores, and processes medical imaging data from devices worldwide, enhancing interoperability and data accessibility across hospitals and health systems.AWS services used include Amazon SageMaker for machine learning and deep learning capabilities, Amazon Simple Storage Service (S3) for storage, Amazon Elastic Compute Cloud (EC2) for compute infrastructure, AWS Service Catalog for application deployment, and Amazon Cognito for user authentication and security.

GE HealthcareHealthcare

Adspert, a Berlin-based ISV, developed a pricing tool to optimize product prices dynamically on ecommerce marketplaces to maximize product visibility and seller profits.Challenges included the need for near-real-time pricing decisions to increase product visibility amidst rapidly changing prices.The solution used Amazon SageMaker to train and deploy a Scikit-Learn Random Forest model predicting product visibility based on competitive pricing and other factors.AWS Glue performed ETL and data preparation, AWS Lambda optimized price recommendations, and Amazon RDS, S3, and SQS were used for data management and processing.The architecture enabled automated training and near-real-time inference to recommend optimal prices balancing sales volume and margins, increasing seller profitability.

AdspertRetail

Edelweiss Tokio Life Insurance Company Ltd, a life insurance company in India, built a data-driven cross-sell solution to replace rule-based recommendations that were producing irrelevant offers and missing conversion opportunities.The implementation used Amazon SageMaker to train and tune a CatBoost-based cross-sell propensity model, used a separate SVD-based policy recommendation model, and added frequent pattern mining to validate popular policy bundles.The team processed about 100,000 records with more than 200 attributes, standardized the training and batch inference workflow with SageMaker managed training, automatic model tuning, ECR-hosted custom containers, notebooks, and batch transform, and deployed the model in production for batch scoring.

Edelweiss Tokio Life InsuranceInsurance

Brillio partnered with Microsoft to deliver advanced analytics and predictive maintenance using Azure Machine Learning, HDInsight, Power Platform, and Azure IoT across manufacturing and retail sectors.The solution enabled a Midwest retailer to gain deep buyer-behavior insights, optimizing inventory and delivering superior customer value through machine learning models interpreting large volumes of purchasing data.Brillio’s clients benefitted from rapid deployment, robust integration, and seamless managed services delivered via Microsoft’s cloud platform.The machine learning-powered system also analyzed sensor data from manufacturing equipment to detect anomalies, enabling predictive maintenance and reduced downtime.Brillio’s focus on industry-specific, repeatable solutions enhanced operational efficiency and speed to market for multiple enterprise customers.Their managed services model, enabled by Microsoft’s partnership and CSP model, allowed clients to move quickly without managing complex subscriptions.Significant staff training in Microsoft technologies ensured solution quality and innovation.Brillio’s investments in IoT and AI have positioned it as a leader delivering value in fast-evolving environments like manufacturing and retail.

Midwest RetailerManufacturing

RELEX Solutions uses Google Cloud to optimize retail promotion management, improving profit margins and reducing waste.Their platform processes vast retail datasets using BigQuery, Cloud Storage, Dataflow, and Google Kubernetes Engine.The forecasting models were migrated to Vertex AI for MLOps capabilities, and an AI agent built on Gemini and orchestrated with GKE enables natural language interaction and campaign automation.

RELEX SolutionsRetail