EnterpriseAIBubble

AI Resume Parser

A hiring process that took days reduced to 2 hours. Built in 4 weeks for a global advisory firm operating across 6 countries.

50 to 300 resumes per position. Five manual review stages. Dozens of active projects running simultaneously. The process was unsustainable and we were brought in to fix it.

Scope my build, free, 48 hrs

2 Hours

hiring cycle time

50–300

resumes per position

5 → 1

review stages eliminated

4 weeks

build and deployment

Brief

The Brief

A global advisory firm supporting economic development across 6 countries needed to fix a hiring process that was taking days per position across dozens of simultaneous projects. We mapped the full workflow, recommended replacing the existing approach entirely, and built a private AI recruitment engine in 4 weeks.

Timeline

Built and deployed in 4 weeks. Still in active use.

The Problem

The firm was processing 50–300 resumes per position across dozens of simultaneous hiring cycles. Five manual review stages each a human bottleneck meant every hire took days. With large-scale contractual projects across 6 countries depending on the right people being hired fast, the process was a structural risk.

“The firm was processing 50–300 resumes per position across dozens of simultaneous hiring cycles.”

What they asked for. What we recommended instead.

Original brief

Our recommendation

Original brief was to fix an existing Sage integration. After mapping the full hiring workflow end to end, we recommended starting from scratch the bottleneck was the manual effort at every stage, not the software. A patch would not have solved it.

Build

What We Built

01
Automatic resume parsing into firm's standard format any input format accepted
02
Private OpenAI instance hosted on client infrastructure zero data exposure
03
Dynamic keyword, skill, and experience screening against hiring criteria
04
Automatic candidate ranking by match score
05
Microsoft Calendar integration interview slots matched to both parties automatically
06
Interviewer remarks and transcript logging on dashboard
07
Automated candidate progression through each stage
08
Director-facing shortlist of 3 final candidates
09
Full hiring pipeline visible per position and per project

The Results

2 Hours

hiring cycle time

50–300

resumes per position

5 → 1

review stages eliminated

4 weeks

build and deployment

“You boys are one of the smartest people I've met in my 50 years of doing this.”

10 min read

How to Build an MVP That Actually Works A No-Code Founder's Guide

Learn how to build an MVP that validates fast, attracts users, and impresses investors. The exact framework Wolf Nocode Studio uses across 25+ Bubble and AI-powered product builds.

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