Building Cntrlall: How Sourcing Analytics Works

I built Cntrlall because I was tired of managing spreadsheets, copy-pasting candidate notes, and manually updating pipeline stages across different tools. It is designed as a recruiter's workspace: a place to structure candidate context, compare role requirements, and keep the sourcing process cleaner.

Resume Keywords vs. Semantic Understanding

Standard recruiting software uses basic keyword matching. If a job spec asks for "React", the software looks for the word "React". But keyword matching is shallow. A bootcamp graduate might list "React" next to a senior developer with 8 years of production React experience. Cntrlall utilizes semantic understanding to read between the lines.

"Keywords tell you what a candidate has listed. Semantic matching tells you what they have actually built and their true depth of experience."

Architecture and Heuristics

Cntrlall parses raw profiles and maps them against job specs using three key heuristics:

• Complexity Factor: Analyzes candidate tenure, scale of systems built, and ownership details in previous roles.
• Toolchain Match: Looks at actual ecosystem usage (e.g. state management, CI/CD pipelines) rather than just language tags.
• Velocity Index: Measures how quickly a candidate progresses in their career and maps their growth indicators.

Cntrlall is a tool built by a recruiter, for recruiters. The product idea is simple: reduce scattered work, make candidate review more structured, and leave the important judgment with the human doing the hiring work.