Sales AI Use Case Ranking

Vxceed, a global SaaS provider for consumer packaged goods sales and distribution, built a near real-time AI platform on AWS to improve store-level visibility and execution for retail-focused organizations.,The platform interprets store signals, produces actionable guidance for commercial teams, and generates AI news bulletins with audio and video.

Fastagger, an African deep-tech startup, has developed a mobile AI business assistant to empower small and medium businesses (SMBs) in Africa. Addressing the challenge of unreliable internet and limited digital infrastructure, Fastagger’s solution runs AI models efficiently on affordable smartphones without requiring a continuous connection. The AUNI system is embedded into Safaricom’s M-PESA Business App, supporting over 2,500 MSMEs in Kenya. This on-device agent enables customer engagement automation, loyalty management, and business coaching.,The AI assistant reduces previously manual processes from eight steps to just two, driving operational efficiency and customer retention. Microsoft’s Africa Transformation Office and NVIDIA have supported Fastagger with mentorship and resources, accelerating the deployment of this mobile-based AI. Key partnerships and the integration with tools like Azure AI, Azure IoT, and GitHub enable robust on-device machine learning. Real-world results underscore substantial improvements in SMB engagement, financial tracking, and growth opportunities, enhancing digital access for underserved populations.,By decentralizing access to AI, Fastagger brings business intelligence and automation to bandwidth-constrained and rural environments—making it easier for SMBs to track customer data, streamline marketing, and make data-driven decisions. The SaaS product costs just $1 to $5 per month, making advanced technologies affordable for local entrepreneurs.,The project illustrates how Microsoft technologies and strategic partnership can close Africa’s digital divide, offering repeatable digital business models to other regions. Fastagger’s infrastructure is available globally via Azure, expanding its impact beyond Africa. Participant feedback validates the significant value of democratized, mobile-first AI for emerging markets.

Chow Tai Fook Jewellery Group standardized on Microsoft 365 E5 and Microsoft Purview, then used Microsoft Azure OpenAI Service, Microsoft Fabric, GitHub Copilot, and a Copilot ecosystem to embed AI across luxury retail operations.,The company deployed more than 400 customized AI agents, built a closed-loop AI empowerment system for diagnosis, training, and real-time execution, created a hyper-aware omnichannel AI engine linking online intent to inventory-backed recommendations, and introduced a natural-language AI Insights Platform for management.

Fujitsu faced time-consuming and manual sales proposal creation processes, hampering staff productivity and slowing the onboarding of new salespeople. To address these challenges, Fujitsu developed an orchestrated multi-agent AI system using Microsoft Azure AI Agent Service, Azure AI Foundry, and Semantic Kernel, allowing them to automate data gathering and proposal drafting. The new system integrates with Fujitsu's existing workflows and leverages multiple specialized AI agents to dynamically retrieve, synthesize, and tailor sales proposals from dispersed enterprise data sources. As a result, Fujitsu boosted sales team productivity by 67%, enabling staff to focus on customer engagement, faster onboarding for new hires, and delivery of more accurate, data-driven, and current proposals.

RSM deploys advanced Copilot Agents in manufacturing to reduce quality risks and manage product recalls.,AI-powered agents analyze real-time data, identify affected product batches, pinpoint root causes, and automate recall notifications—all with seamless integration to existing Quality Management Systems (QMS), ERPs, and CRM tools.,Their technical architecture includes layering data sources, Copilot intelligence (Copilot Studio, Power Platform, Power Automate), and user interfaces in Teams, Outlook, or Dynamics 365.,AI models and Copilot Studio guide agents through user prompts, system actions, and automated event triggers. Security is ensured via Entra ID authentication, data loss prevention, and role-based access for generative AI.,Retrieval-Augmented Generation (RAG) capabilities allow accurate processing for both structured (quality orders, ERP records) and unstructured (documents, feedback) data.,Governance processes retain humans-in-the-loop for decisions with validation, filters for sensitive topics, and performance monitoring, ensuring compliance and reliability.,These innovations accelerate investigations and recalls, improve regulatory alignment, and protect corporate brands in a highly regulated environment.,RSM offers custom Copilot solutions for manufacturers seeking operational transformation and competitive advantage.

Verdantas is an integrated environmental science, engineering, and consulting firm that grew rapidly through acquisitions, creating disconnected systems and data.,The company designed an agent in Copilot Studio and used Microsoft Fabric to unify data across the organization.,The agent supports employees with proposal development, technical resource search, project and client intelligence, and resource optimization.,Verdantas also built a contract management agent that reviews uploaded contracts against legal policy stored in SharePoint to identify escalation clauses and negotiation points.,Multi-agent orchestration in Copilot Studio routes requests to sub-agents by data source and improves response speed.

OPLOG, a technology-driven fulfillment company, built a production-ready business intelligence system using AI agents deployed on Amazon Bedrock AgentCore.,The solution processes business transactions autonomously across sales pipeline management, data quality enforcement, and prospect research, integrating HubSpot, Microsoft Teams, Amazon S3, and Amazon Bedrock Knowledge Bases.

IBM faced major productivity drag across HR, procurement, IT, supply chain, sales, and tax because employees spent time searching for policies, navigating siloed systems, handling routine support, and manually aggregating data.,IBM set out to create an enterprise-wide productivity blueprint using AI, hybrid cloud, and automation, with domain assistants such as AskIT, AskHR, and AskSales deployed across workflows.

Artificial Labs used Google Cloud to build insurance claims automation that recognizes patterns in complex insurance documentation and moves risks toward quote readiness with humans in control.,Conscium, Artificial Labs, and Oxford Quantum Circuits also used Google Cloud to manage thousands of LLM requests efficiently and support adjacent AI evaluation and quantum workloads.,The implementation centers on Gemini Enterprise Agent Platform, Gemini for Google Cloud, and BigQuery as the data and analytics foundation.

Worldbox is a Swiss business intelligence company with a database of more than 400 million businesses worldwide.,It partnered with AllCloud to design a secure, two-tiered data distribution model on AWS Marketplace that lets customers search, discover, and purchase data using agentic AI tools.,The solution adapts Worldbox’s existing API interface to agentic AI workflows through a Model Context Protocol (MCP) server.

Poloplast modernized a legacy AS/400 ERP-based planning process by integrating demand planning, business performance planning, automation, and AI agent capabilities across finance and operations.,The company uses Microsoft Dynamics 365 Supply Chain Management, Dynamics 365 Finance, Power Platform, and Microsoft Copilot Studio to improve forecasting, budgeting, reporting, and employee access to knowledge.

Aily Labs built a mobile-first decision intelligence platform for enterprise users across pharmaceutical, retail, consumer goods, and other sectors.,The platform’s AI brain coordinates hundreds of classical ML models, LLMs, and thousands of enterprise agents orchestrated by a Super Agent to surface insights and actions in real time.,Aily Labs uses AWS infrastructure including Amazon Bedrock, Amazon EKS, Amazon S3, Amazon RDS, AWS KMS, and AWS security/auditing services, and uses Bedrock Prompt Caching to reduce recomputation and latency.

Carousell Group, a multi-category classifieds and recommerce marketplace, used Google Cloud generative AI and data services to improve seller listing creation, scale fraud analysis, and automate internal workflows.,The company built a new "List with AI" experience that lets sellers upload a short video or photos and uses Gemini's multimodal capabilities to generate listing titles, descriptions, category, price, condition, and style variants for review.,Carousell also moved fraud model bulk inference to an integrated BigQuery and Vertex AI workflow so it can analyze its full chat dataset and iterate much faster than before.,Internally, Carousell created a Gemini-based translation workflow and a secure Slack bot that answers HR questions from policies stored in Google Drive.

Qualia provides closing software to thousands of title and escrow companies that help consumers complete home purchases and sales.,The company built Qualia Clear, an agentic AI system that automates review, analysis, and execution of title and escrow workflows using Google Cloud AI.

Unilever, a global consumer goods company, faced the challenge of complicated website navigation and low conversion rates due to customers struggling to find products and information efficiently. In partnership with Capgemini and Microsoft, Unilever implemented a multi-agent AI system built on Microsoft Azure, orchestrating a suite of specialized AI agents to deliver seamless, contextual, and multi-language customer experiences on their e-commerce platform.,The multi-agent system leverages Azure AI, Azure OpenAI (GPT-4), Azure AI Search, Cosmos DB, and PromptFlow to power natural language interactions, personalized product recommendations, and adaptive global language support. An orchestrator agent intelligently routes queries to the right agent, while retrieval-augmented generation (RAG) enables the system to combine internal product and recipe data with external generative models for accurate, real-time responses.,Key safety guardrails were implemented, including robust content moderation and prompt restrictions, ensuring secure interactions across use cases. The solution not only enhanced discovery and recommendation features but also improved order fulfillment by integrating with back-end shopping cart workflows.,Notable business outcomes include faster and more accurate query responses, increased user engagement, improved conversion rates, and a frictionless global user experience, setting a new e-commerce standard for digital customer care.

Retailers worldwide are adopting agentic AI to transform customer and store associate experiences. Swedish retailer Lindex has rolled out a custom Copilot to deliver contextually relevant, AI-guided support for store associates, boosting efficiency and service quality. Kappahl utilizes Store Operations Agent, a generative AI solution providing secure, on-demand answers to product and store policy questions, expediting decision-making on the sales floor. The deployment is underpinned by Microsoft’s Cloud for Retail, Azure AI Foundry, and Copilot Studio, with over 1,400 prebuilt connectors for rapid retail-scale AI customization. The solution empowers associates, optimizes operations, personalizes shopper journeys, and enables scalability for growth across global retail contexts.

Hedvig replaced siloed data infrastructure with a unified semantic layer using Looker and BigQuery to enable self-service analytics.,Implemented advanced data workflows with dbt and Vertex AI for predictive pricing models and AI-ready data structure.,Democratized data access across claims, underwriting, and sales teams, reducing manual report generation.,Exploring conversational AI to allow natural language queries on self-explainable data models.,Achieved rapid claim processing and scalable analytics without increasing data team headcount.

Satellite giant EchoStar needed more efficient operations to deliver content to businesses and consumers globally. Its Hughes division wanted to increase employee efficiency and streamline daily business processes.,Using Microsoft Azure AI Foundry, Hughes developed 12 new production apps, from automated sales call auditing and customer retention analysis to field services process automation support and more.,The solutions currently in production are expected to save Hughes more than 35,000 work hours annually and boost workforce productivity by at least 25%.,EchoStar delivers entertainment, communication, and connection to millions of businesses and consumers around the world through leading satellite-powered brands, including Hughes Network Systems, DISH, Sling, and Boost Mobile.,The company aims to provide these services reliably and expand on its mission to offer satellite coverage in hard-to-reach rural areas. That’s why EchoStar and its brands take a technology-forward approach to solving complicated operational, productivity, and customer experience inefficiencies.,An avid and early AI adopter, Hughes Network Systems understood the power of generative AI to address challenges in speech, vision, text, and structured data for a wide range of work productivity challenges. It needed a way to relieve sales call auditors from listening to hours of conversations to ensure quality communications, a priority customer experience objective at Hughes.,The company knew it was an area in which it could significantly improve cost, productivity, and ROI by using the right technology.,Hughes chose Microsoft Azure AI Foundry because of their longstanding partnership with Microsoft and its deep technical knowledge. They relied on Microsoft’s approach to responsible AI and data privacy, security, and governance options.,Hughes developed an AI-driven, automated speech-to-text system, delivering higher-value interactions and advanced call insights and agent directives across calls, exponentially boosting productivity.,They also created a large language model (LLM) operations framework using Azure AI Foundry to evaluate and ensure the quality and safety of AI-generated outputs. This helped accelerate moving from pilot to production.,Multiple AI applications enhance employee efficiency and customer service at Hughes, saving over 30,000 hours annually summarizing calls and 8,000 hours through field services process automation.,AI-enhanced computer vision accelerates image generation and annotation for faster training and higher accuracy of traditional vision models.,Retrieval-augmented generation (RAG) improves information accessibility for employees and field installers.,AI analyzes customer journey data for quality assurance and churn reduction, boosting overall productivity by 25%.,Hughes plans to expand agentic AI deployment using Azure AI Foundry and Microsoft Copilot Studio across verticals to continue AI innovation.

OneAssure is a Bengaluru insurtech platform in India that simplified health insurance workflows using Google Cloud AI.,The company used Document AI to extract structured information from unstructured policy PDFs and deployed the solution on Google Kubernetes Engine.,It also used Gemini Enterprise Agent Platform to support product and policy Q&A, coverage gap analysis, and a Gemini-powered D2C chatbot for real-time policy assessments.

Vernost Tech Ventures Pvt. Ltd. built an intelligent customer engagement suite to make travel and holiday booking experiences faster and more personalized for its banking and aviation clients.,The company used AWS-hosted generative AI and machine learning services to support customer Q&A, pre-booking recommendations, booking assistance, and post-booking automation across the travel journey.