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The goal was to deploy an Agentic AI workflow that could validate returns on arrival, classify condition and root cause independently, recommend the optimal disposition path, and route for approval only where value thresholds required human sign-off, turning returns from a cost center into a recoverable asset
A leading bank in the Middle East aimed to gain a unified view of competitor campaigns and customer & partner interactions across fragmented digital channels, while improving campaign effectiveness through real-time, insight-driven decision-making. The client also wanted to focus on better understanding customer sentiment and needs to drive higher marketing ROI, sharper targeting, and increased cross-sell opportunities.
A leading global FMCG company was losing significant value across its warehouse and DC network due to persistent picking errors and mislabeling incidents. Wrong items dispatched, incorrect quantities fulfilled, and labels mismatched to SKUs were creating a downstream ripple: retailer chargebacks, costly reverse logistics, and eroded service levels. The disposal and correction process was entirely manual: warehouse supervisors would physically verify each reported error, trace it back to the pick event, reconcile it with the WMS, and initiate a corrective action, a process that took days and relied heavily on individual judgment.
A leading global consumer goods company was experiencing recurring inventory waste across its warehouse and distribution network, ageing stock sitting past shelf-life thresholds, quantity mismatches between WMS and ERP systems, and disposal decisions that were slow, inconsistent, and largely reactive.
The client’s organization had been growing in size and complexity, creating the need for a cohesive, secure, and scalable workforce analytics foundation. As the organization scaled, its People & Organization (P&O) analytics relied on multiple legacy Power BI dashboards across business verticals. While informative, this setup limited leadership’s ability to gain a unified, real-time view of workforce health and take timely action.
The company’s digital marketing team needed to produce a high volume of diverse, high-quality content (50-100 assets per month) across multiple formats (blogs, articles, white papers, infographics, expert reviews, tweets, etc.) while ensuring brand consistency, data compliance, and personalized messaging. Their existing workflow was manual, time-consuming, and lacked the scalability to meet their growing content demands.
Manual CI workflows consumed significant analyst time, limiting productivity and scalability. Limited human bandwidth restricted real-time, comprehensive coverage across competitors, markets, and geographies. These manual processes also led to data inconsistencies, missed signals, and slower decision-making. As a result, traditional CI lacked the agility and personalization needed for effective strategic response.
A leading global beverage brewing company sought to enhance their logistics reliability and operational efficiency across their supply chain. The goal was to reduce manual intervention, accelerate anomaly resolution, and enable real-time visibility across the brewery-to-distribution center network through an Agentic AI–powered alert generation and resolution platform.
The client’s Finance and P&O teams lacked a single, automated view of full-time employees (FTE) and headcount to support workforce cost governance. To address the need for consistent, auditable, and decision-grade workforce insights, the organization set out to establish a unified FTE reporting capability across Finance and P&O. This initiative focused on eliminating manual reconciliation, improving data accuracy, and enabling leadership to track headcount against cost and workforce targets.
