Manual sales audits cost $26/hour. AI speech analysis cut costs to $2, saving 35,000 annual work hours.
A global satellite communications provider serves millions of businesses and consumers, specifically targeting hard-to-reach rural areas.
Sales call auditors spent hours manually listening to conversations to ensure communication quality, a process that cost $26 per call. This manual...
“We chose Microsoft Azure AI Foundry because of our longstanding partnership with the company and its deep technical knowledge. We rely on Microsoft’s approach to responsible AI and its data privacy, security, and governance options.”
Hughes Network Systems's Call center automation is part of this use case:
Satellite broadband and managed network services for enterprise and residential use.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Reps lost time hunting across complex systems. Now, AI agents surface verified answers and automate notes, freeing humans to connect.
Saturated queues kept customers waiting. AI now handles the overflow, resolving 40% of calls and freeing staff for complex cases.
Sales reps spent 50% of prep time hunting for internal knowledge. Now, AI automatically extracts and summarizes relevant slides.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Manual reviews bottlenecked insights. Now, models transcribe and score calls to trigger automated follow-ups.
Reps manually calculated variances across three systems. AI now compares statements in seconds, spotting fee changes instantly.
Manual fine-tuning held back deployment. Automated optimization cut inference time 63% and agent routine work by over 50%.
Inboxes overflowed with tracking and sizing queries. An AI now locates orders and asks player height to size gloves instantly.
Specs scattered in PDFs meant fixes took weeks. Now, autonomous agents access unified data to resolve over 25% of cases instantly.
Manual sales audits cost $26/hour. AI speech analysis cut costs to $2, saving 35,000 annual work hours.
A global satellite communications provider serves millions of businesses and consumers, specifically targeting hard-to-reach rural areas.
Sales call auditors spent hours manually listening to conversations to ensure communication quality, a process that cost $26 per call. This manual...
“We chose Microsoft Azure AI Foundry because of our longstanding partnership with the company and its deep technical knowledge. We rely on Microsoft’s approach to responsible AI and its data privacy, security, and governance options.”
Hughes Network Systems's Call center automation is part of this use case:
Satellite broadband and managed network services for enterprise and residential use.
Enterprise software, cloud infrastructure, and consumer electronics platform.
Related implementations across industries and use cases
Reps lost time hunting across complex systems. Now, AI agents surface verified answers and automate notes, freeing humans to connect.
Saturated queues kept customers waiting. AI now handles the overflow, resolving 40% of calls and freeing staff for complex cases.
Sales reps spent 50% of prep time hunting for internal knowledge. Now, AI automatically extracts and summarizes relevant slides.
Agents typed furiously while customers waited on hold. AI now summarizes calls, saving the team 250,000 hours annually.
Manual reviews bottlenecked insights. Now, models transcribe and score calls to trigger automated follow-ups.
Reps manually calculated variances across three systems. AI now compares statements in seconds, spotting fee changes instantly.
Manual fine-tuning held back deployment. Automated optimization cut inference time 63% and agent routine work by over 50%.
Inboxes overflowed with tracking and sizing queries. An AI now locates orders and asks player height to size gloves instantly.
Specs scattered in PDFs meant fixes took weeks. Now, autonomous agents access unified data to resolve over 25% of cases instantly.