AI Automation

HireSort: Resume Screening Automation

Parses resumes, scores candidates against job criteria, and schedules interviews automatically.

Client

TalentLink Recruiting

Industry

HR / Recruitment

Duration

4 weeks

Biggest result

-60%

recruiter time

Overview

Parses resumes, scores candidates against job criteria, and schedules interviews automatically.

The Challenge

TalentLink Recruiting was processing 500+ resumes per open position. Their recruiters spent 60% of their time on initial screening — reading resumes, checking qualifications, and scheduling interviews. The process was slow, inconsistent, and prone to unconscious bias.

Our Solution

We built HireSort, an automated resume screening pipeline. When a job posting goes live, incoming resumes are parsed with Python, and OpenAI embeddings score each candidate against the job criteria — skills, experience, education, and relevance. Top candidates are automatically invited to schedule interviews via Calendly through Zapier. Recruiters see a ranked dashboard with structured scores instead of raw resumes.

See it in action

See the automation pipeline light up step by step — from trigger to output.

Automation Pipeline

Job Posted

Resume Parsing

AI Scoring

Auto-Invite

Ranked Dashboard

Before vs After

Drag the slider to compare the old process with the new one.

Before

3 min

Screening time/resume

After

under 1 sec

Screening time/resume

Screening time/resume

Before

3 min

→

After

under 1 sec

Resumes reviewed

Before

40% of total

→

After

100% of total

Time to first interview

Before

5 days

→

After

1 day

Results

0%

Faster screening

0%

Less recruiter time

0

Scoring method

Improvement visualization

Faster screening75%
Less recruiter time-60%
Scoring methodUnbiased

Key Features

  • Automated resume parsing with structured data extraction
  • AI-powered candidate scoring against job-specific criteria
  • Unbiased structured scoring to reduce hiring bias
  • Automatic interview scheduling via Calendly integration
  • Ranked candidate dashboard with score breakdowns

Tech Stack

PythonOpenAI embeddingsZapierCalendly

Project Timeline

1

Discover

3 days

Analyzed screening workflow, bias concerns, and interview scheduling.

2

Build

16 days

Built resume parser, embedding-based scoring, Calendly integration.

3

Launch

3 days

Deployed for first job posting, tested scoring accuracy with senior recruiters.

4

Optimize

Ongoing

Refine scoring criteria per role, monitor for bias, tune thresholds.

"We screen 500 resumes per role now without a single person reading them all. The AI ranks them objectively and our recruiters focus on the top 20%. Hiring is 60% faster."
P

Priya Sharma

Talent Director, TalentLink Recruiting

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