Hughes Accelerates Operations Efficiency with Microsoft Azure AI Foundry

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.