Redaction stripped context, forcing agents to rebook tickets. Native security now lets AI resolve complex requests without a handoff.
An AI-native platform provider for the world's largest organizations, managing end-to-end voice and digital contact center conversations at enterprise scale.
A mandatory PII redaction layer created latency and stripped essential context from user data, making complex tasks like airline ticket rebooking...
“It’s a bit of a headache when you’re working on a customer deployment and you see that GenerativeAgent would provide even better responses if it had more data to draw on.”
Generative AI platform for contact center automation and customer experience.
Cloud computing platform and on-demand infrastructure services.
ASAPP's Contact center automation is part of this use case:
Related implementations across industries and use cases
Raw pace and power data overwhelmed users. AI now turns millions of daily uploads into instant, encouraging performance insights.
Agents were buried in common questions, with resolutions taking 3 hours. Now, an AI agent fields FAQs, freeing experts for complex cases.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Callers instantly bypassed robotic routing. Now, an AI voice agent resolves routine requests, passing full summaries to human reps.
Untangling 30-call AI interactions consumed developers. Now, support teams use system traces to resolve context issues without engineers.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
Redaction stripped context, forcing agents to rebook tickets. Native security now lets AI resolve complex requests without a handoff.
An AI-native platform provider for the world's largest organizations, managing end-to-end voice and digital contact center conversations at enterprise scale.
A mandatory PII redaction layer created latency and stripped essential context from user data, making complex tasks like airline ticket rebooking...
“It’s a bit of a headache when you’re working on a customer deployment and you see that GenerativeAgent would provide even better responses if it had more data to draw on.”
Generative AI platform for contact center automation and customer experience.
Cloud computing platform and on-demand infrastructure services.
ASAPP's Contact center automation is part of this use case:
Related implementations across industries and use cases
Raw pace and power data overwhelmed users. AI now turns millions of daily uploads into instant, encouraging performance insights.
Agents were buried in common questions, with resolutions taking 3 hours. Now, an AI agent fields FAQs, freeing experts for complex cases.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Callers instantly bypassed robotic routing. Now, an AI voice agent resolves routine requests, passing full summaries to human reps.
Untangling 30-call AI interactions consumed developers. Now, support teams use system traces to resolve context issues without engineers.
Scattered data and basic coding tools bottlenecked engineers. A 9-agent AI workflow shifts them from writing code to directing AI teams.
Sequential AI testing bottlenecked development. Engineers built a concurrent, code-first pipeline to evaluate agent responses in seconds.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.