Automating repository code reviews with multi-rubric LLM radar charts, calculating real-time skill vector complementarity distance, and dispatching instant AI mentor triage.
*Benchmark metrics based on sample seeded dataset and live inference latency
Select an engine module below to preview live operational capabilities.
Evaluates code repositories across Innovation, Technical Complexity, Completeness, and UX. Inspects actual source files, file tree structures, and test suites to generate visual Recharts radar charts and executive judge feedback.
Open AI Evaluation WorkbenchExisting registration platforms track RSVPs but leave code quality, team formation, and mentor triage unmanaged.
From registration to final leaderboard locking in 4 automated steps.
Participants sign in and create skill vector profiles highlighting tech stacks and experience.
Complementarity matrix pairs solo developers into balanced, highly functional hackathon rosters.
Google Gemini & Groq inspect GitHub repos, READMEs, and file trees to compute multi-rubric radar scores.
Judges review radar charts, lock final evaluation scores, and export markdown summaries for prize allocation.
Everything needed to run production-grade hackathon operations.
Scores projects across Innovation, Technical Complexity, Completeness, and UX with Recharts visual radar charts.
Matches complementary participants based on tech stack vector distance and skill deficit alerts.
Resolves technical questions instantly and schedules video sessions with specialized mentors.
Browse submissions with Grid/List views, search filters, file tree inspectors, and live project additions.
Export clean, formatted markdown evaluation reports for organizers, judges, and sponsor track sponsors.
Input your own Google Gemini API key under Settings to run unlimited custom LLM evaluations.
Experience real-time Gemini AI evaluations, vector complementarity team matching, and instant mentor triage right now.