Acticio analyzes proof-of-work signals across GitHub, portfolios, and shipped projects to help hiring teams identify real builders beyond AI-optimized resumes - so recruiters spend time interviewing candidates with real ownership signals, not just keyword matches. AI increased applicant volume, but not necessarily applicant quality. Acticio helps hiring teams investigate real proof-of-work signals before spending hours interviewing the wrong candidates.

DigitalOcean Serverless Inference — 55+ AI models behind one OpenAI/Anthropic-compatible API

55+ AI models behind one OpenAI/Anthropic-compatible API

Hey Product Hunt 👋 Over the last year, we noticed something changing in hiring: Candidates can now generate highly optimized resumes in minutes using AI. Most ATS systems still rank applicants based on: - keyword matching - formatting - buzzwords - resume optimization But none of that proves someone actually built the work they claim. We started building Acticio after seeing hiring teams drown in polished applications that all looked qualified on paper - especially for technical roles. Instead of only reading resumes, Acticio analyzes proof-of-work signals across: - GitHub activity - portfolio projects - deployed apps - contribution consistency - ownership patterns - linked work inside resumes The goal isn’t to replace interviews or ATS systems. It’s to help recruiters and founders spend less time filtering keyword-matched noise and more time interviewing candidates with real execution signals. One thing we learned while talking to recruiters and founders: The hiring bottleneck is no longer finding applicants. It’s filtering signal from noise. Still early, but excited to hear feedback from recruiters, founders, engineers, and anyone hiring in the AI resume era 🙌

DigitalOcean Serverless Inference — 55+ AI models behind one OpenAI/Anthropic-compatible API

55+ AI models behind one OpenAI/Anthropic-compatible API

Acticio

Proof-of-work analysis for modern hiring

Proof-of-work analysis for modern hiring