Repetitive manual entry slowed hiring. Resume auto-fills and AI-drafted posts cut writing time 67%, boosting submissions 12%.
A job-search platform in Taiwan serving 13 million users relied on a legacy colocated data center to connect 4 million corporate clients with 9 million job seekers.
Job seekers faced a repetitive application process requiring them to complete duplicate fields multiple times, while the legacy search infrastructure...
“Job seekers had to go through extensive filtering, and finding a suitable job match took too long.”
Online recruitment platform and human resources services in Taiwan.
Cloud computing platform and on-demand infrastructure services.
Helped 1111 Job Bank adopt Amazon Personalize and OpenSearch to enhance search efficiency.
Related implementations across industries and use cases
Sorting variable-fit CVs bottlenecked recruiters. A serverless Llama 2 pipeline now ranks matches in seconds, cutting review time 95%.
Keyword matching confused titles with reporting lines. Vector embeddings now capture intent, matching concepts rather than exact strings.
Keyword search failed on unconventional resumes. Semantic matching interprets intent, boosting job applications by 20%.
SSetup and data analysis held back shops for weeks. AI now runs those workflows, helping merchants land their first sale in days.
Serial testing bottlenecked development. Now, parallelized checks validate hundreds of complex conversation paths in seconds.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.