Teams struggled to label millions of multilingual call reports. Gen AI now labels calls automatically with nearly 100% accuracy.
A global trust technology company operating the Whoscall app with over 100 million users and the largest telephone number database in East and Southeast Asia containing 2.6 billion entries.
Employees manually labeled phone numbers that the database missed, a process that became unsustainable with millions of daily user reports across...
“We love AWS managed services because they reduce our operations and maintenance costs and help automate security checks—making it easier to scale globally and securely as we grow.”
TrustTech platform for scam detection and digital identity protection.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Standard tools mislabeled 1 in 5 reviews. By routing tasks to specialized models, the system now delivers trusted, nuanced insights.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Standard OCR failed on complex layouts. Vision-language models now automate matching, cutting validation effort by 40%.
Analysts manually reviewed mountains of data for every alert. Now, AI agents summarize and verify facts, boosting efficiency by ~20%.
Agents manually checked data across scattered systems. AI now scans unstructured evidence in seconds, boosting fraud detection 6x.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.
Teams struggled to label millions of multilingual call reports. Gen AI now labels calls automatically with nearly 100% accuracy.
A global trust technology company operating the Whoscall app with over 100 million users and the largest telephone number database in East and Southeast Asia containing 2.6 billion entries.
Employees manually labeled phone numbers that the database missed, a process that became unsustainable with millions of daily user reports across...
“We love AWS managed services because they reduce our operations and maintenance costs and help automate security checks—making it easier to scale globally and securely as we grow.”
TrustTech platform for scam detection and digital identity protection.
Cloud computing platform and on-demand infrastructure services.
Related implementations across industries and use cases
Standard tools mislabeled 1 in 5 reviews. By routing tasks to specialized models, the system now delivers trusted, nuanced insights.
Model tuning took weeks, slowing market entry. On Bedrock, updates take days, cutting costs 50% and boosting retention 75% for telecom.
Standard OCR failed on complex layouts. Vision-language models now automate matching, cutting validation effort by 40%.
Analysts manually reviewed mountains of data for every alert. Now, AI agents summarize and verify facts, boosting efficiency by ~20%.
Agents manually checked data across scattered systems. AI now scans unstructured evidence in seconds, boosting fraud detection 6x.
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.
On-premise systems, dispersed and brittle, bottlenecked every release. AI agents now run routine dev steps — hours cut to minutes.
A mistranslated word could derail global R&D projects. Now, researchers instantly refine technical papers & communicate seamlessly across languages.