Fork from the Open Library
AIVIA maintains a library of scenario posts — case studies across domains and components. Browse the library, find a scenario close to the role you’re hiring for, and fork it. You can then edit the context pack fields directly — expected background, rubric emphasis, probe style, scenario focus — to match your specific requirements.
Build from Scratch
Submit your job description and AIVIA generates a complete evaluation automatically — scenario, context pack, and evaluation link. Review the output, adjust any context pack fields you want to change, and share when ready.
01 What You Get Either Way
A single evaluation link. Share it anywhere — job boards, LinkedIn, email, your careers page, or posted directly on STEM-Away. Unlimited candidates can use the same link. Each candidate gets a unique evaluation session with adaptive follow-ups and a full report.
Results appear in your dashboard as candidates complete evaluations.
02 Candidate Ownership — And Why It Benefits You
Your context pack remains private — other hiring teams cannot see your configuration. But candidate results are owned by the candidate, even for evaluations you created. You see a candidate’s report only if they toggle it On Resume.
This is one of the most important design decisions in AIVIA. Here’s why it works in your favor:
You attract stronger candidates. Engineers who know they own their results are more willing to take the evaluation seriously. They’re building a portfolio, not just jumping through a hiring hoop. That changes the quality of who shows up.
Every candidate in your search chose to be there. When someone toggles On Resume, they’re signaling confidence in their performance. You’re not sifting through reluctant applicants — you’re seeing people who want to be found based on what they demonstrated.
Results are reusable. A candidate who took your evaluation and toggled it On Resume is now discoverable by other hiring teams too. That means candidates see AIVIA as a career investment, not a one-off screening test. More candidates invest in the platform, more talent accumulates, and your future searches get richer.
Trust drives volume. Platforms that extract candidate data without consent eventually lose their best talent to platforms that don’t. AIVIA’s ownership model keeps the strongest candidates coming back.
For details on context pack fields, see the Context Pack page.