Challenge
AI-Powered Talent Acquisition Platform: Opal Loupe
Opal Search is an innovative talent acquisition platform that streamlines hiring through the use of artificial intelligence, enhancing candidate matching.
Challenges:
- Redesign the existing website.
- Fix bugs and optimize current functionality to enhance the user experience.
- Introduce advanced AI features.
AI-Powered Talent Acquisition Platform: Opal Loupe
Opal Search is an innovative talent acquisition platform that streamlines hiring through the use of artificial intelligence, enhancing candidate matching.
Challenges:
- Redesign the existing website.
- Fix bugs and optimize current functionality to enhance the user experience.
- Introduce advanced AI features.
Solution
Opal Search is an innovative talent acquisition platform that streamlines hiring through the use of artificial intelligence, enhancing candidate matching.
Solutions:
- Redesigned the website and implemented a modern front-end using React, TypeScript, Next.js, and Tailwind CSS, paired with Radix UI for accessible components.
- Integrated AWS Bedrock and OpenAI to generate dynamic filters for candidate searches, enable conversational filters, and fill missing candidate data automatically.
- Prioritized performance optimization to enhance UX and reduce AI-related operational costs by eliminating redundant operations, streamlining backend logic, and sending only essential, pre-processed data to the AI.
Opal Search is an innovative talent acquisition platform that streamlines hiring through the use of artificial intelligence, enhancing candidate matching.
Solutions:
- Redesigned the website and implemented a modern front-end using React, TypeScript, Next.js, and Tailwind CSS, paired with Radix UI for accessible components.
- Integrated AWS Bedrock and OpenAI to generate dynamic filters for candidate searches, enable conversational filters, and fill missing candidate data automatically.
- Prioritized performance optimization to enhance UX and reduce AI-related operational costs by eliminating redundant operations, streamlining backend logic, and sending only essential, pre-processed data to the AI.
Results
- Redesigned the website and implemented a modern front-end using React, TypeScript, Next.js, and Tailwind CSS, paired with Radix UI for accessible components.
- Integrated AWS Bedrock and OpenAI to generate dynamic filters for candidate searches, enable conversational filters, and fill missing candidate data automatically.
- Prioritized performance optimization to enhance UX and reduce AI-related operational costs by eliminating redundant operations, streamlining backend logic, and sending only essential, pre-processed data to the AI.
- Redesigned the website and implemented a modern front-end using React, TypeScript, Next.js, and Tailwind CSS, paired with Radix UI for accessible components.
- Integrated AWS Bedrock and OpenAI to generate dynamic filters for candidate searches, enable conversational filters, and fill missing candidate data automatically.
- Prioritized performance optimization to enhance UX and reduce AI-related operational costs by eliminating redundant operations, streamlining backend logic, and sending only essential, pre-processed data to the AI.