Staff manually searched websites for 30 minutes per report. AI now scours the web to build interview guides in five minutes.
A Brazilian nonprofit organization helps low-income youth enter the labor market by providing career guidance and job placement support.
Staff spent 30 minutes on average per student report manually searching websites and compiling interview preparation documents. This labor-intensive...
“Llama is a core component of our AI-powered solution to enhance the efficiency of our job preparation process for young candidates. We chose Llama 3.1 primarily because of its seamless integration with our existing infrastructure on Oracle Cloud Infrastructure, where all of our solutions are hosted. We needed a model that could efficiently leverage OCI’s capabilities, including its scalability and performance for AI workloads.”
Non-profit providing job training and career placement for low-income youth in Brazil.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Instituto PROA's Interview preparation is part of this use case:
Related implementations across industries and use cases
Staff spent 30 minutes compiling one dossier. AI builds it in five, shifting focus from paperwork to career counseling.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Staff spent days reformatting resumes from JPEGs and text messages. Now, AI extracts skills into standard drafts for human review.
Client research took days. An AI agent now compiles tailored briefs in minutes, saving 1,000 hours annually.
Managers spent hours synthesizing reports. AI now drafts briefings 90% faster, saving sales teams an hour daily.
Hiring engineers bottlenecked product development. Using Claude, a non-technical founder now writes code and ships features in hours.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.
Staff manually searched websites for 30 minutes per report. AI now scours the web to build interview guides in five minutes.
A Brazilian nonprofit organization helps low-income youth enter the labor market by providing career guidance and job placement support.
Staff spent 30 minutes on average per student report manually searching websites and compiling interview preparation documents. This labor-intensive...
“Llama is a core component of our AI-powered solution to enhance the efficiency of our job preparation process for young candidates. We chose Llama 3.1 primarily because of its seamless integration with our existing infrastructure on Oracle Cloud Infrastructure, where all of our solutions are hosted. We needed a model that could efficiently leverage OCI’s capabilities, including its scalability and performance for AI workloads.”
Non-profit providing job training and career placement for low-income youth in Brazil.
Social technology company developing AI frameworks, VR hardware, and digital platforms.
Instituto PROA's Interview preparation is part of this use case:
Related implementations across industries and use cases
Staff spent 30 minutes compiling one dossier. AI builds it in five, shifting focus from paperwork to career counseling.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Staff spent days reformatting resumes from JPEGs and text messages. Now, AI extracts skills into standard drafts for human review.
Client research took days. An AI agent now compiles tailored briefs in minutes, saving 1,000 hours annually.
Managers spent hours synthesizing reports. AI now drafts briefings 90% faster, saving sales teams an hour daily.
Hiring engineers bottlenecked product development. Using Claude, a non-technical founder now writes code and ships features in hours.
Fragmented CRM data and manual spreadsheets bottlenecked a lean team. Now, staff use AI to clean records, segment donors, and draft emails.
Training models for 300+ invoice formats bottlenecked operations. Now, generative AI extracts data instantly; staff review exceptions.
QA teams manually searched vast incident logs to assess deviations. Now, multi-agent AI synthesizes past cases into verified summaries.