A call center and rigid FAQ bot couldn't support a multilingual customer base. Now, an AI assistant provides 24/7 help in multiple languages.
Malaysia's national electricity utility serves over 10.5 million customer accounts and operates across the full value chain, including generation, transmission, distribution, and retail.
The utility's centralized call center and a keyword-driven FAQ tool could not meet rising expectations for 24/7 support. The existing systems were...
“This transformation marks a broader shift in how TNB sees its role. With AWS, we're evolving beyond delivering services to building personalized, AI-driven experiences engaging Malaysians on their terms.”
Electric utility company providing power generation and distribution in Malaysia.
Worked alongside TNB to build, configure, and deploy its generative AI assistant SARA
Cloud computing platform and on-demand infrastructure services.
Tenaga Nasional's Customer support is part of this use case:
Related implementations across industries and use cases
Manual checks across 160 games bottlenecked support. GenAI now references player data to resolve 90% of inquiries in minutes.
Service gaps left rural areas behind. AI agents now guide 9M users through 44 tasks on WhatsApp, unifying fragmented support.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Manual call notes burdened agents, while managers struggled to track promises. Now, AI copilots automate summaries and verify commitments.
Managers once manually reviewed up to 84 recordings to find information. Now, AI instantly generates summaries and automated scorecards.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.
A call center and rigid FAQ bot couldn't support a multilingual customer base. Now, an AI assistant provides 24/7 help in multiple languages.
Malaysia's national electricity utility serves over 10.5 million customer accounts and operates across the full value chain, including generation, transmission, distribution, and retail.
The utility's centralized call center and a keyword-driven FAQ tool could not meet rising expectations for 24/7 support. The existing systems were...
“This transformation marks a broader shift in how TNB sees its role. With AWS, we're evolving beyond delivering services to building personalized, AI-driven experiences engaging Malaysians on their terms.”
Electric utility company providing power generation and distribution in Malaysia.
Worked alongside TNB to build, configure, and deploy its generative AI assistant SARA
Cloud computing platform and on-demand infrastructure services.
Tenaga Nasional's Customer support is part of this use case:
Related implementations across industries and use cases
Manual checks across 160 games bottlenecked support. GenAI now references player data to resolve 90% of inquiries in minutes.
Service gaps left rural areas behind. AI agents now guide 9M users through 44 tasks on WhatsApp, unifying fragmented support.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Basic troubleshooting consumed agents' time. Now, an AI fluent in local dialects independently resolves 73% of these cases.
Complex disputes required manual tracing. AI agents now autonomously plan and execute multi-step payment investigations.
Manual call notes burdened agents, while managers struggled to track promises. Now, AI copilots automate summaries and verify commitments.
Managers once manually reviewed up to 84 recordings to find information. Now, AI instantly generates summaries and automated scorecards.
Manually evaluating high call volumes was slow and inaccurate. Now, AI extracts sentiment so sales teams can refine their outreach.
Manual call evaluations delayed insights by weeks. Now, bots score calls at scale, empowering analysts to synthesize data in hours.