The Neural Agency Back to Systems
Public operating example

How a roughly 200-employee services firm recovered 80-100 hours per month.

The firm had multiple branch offices, a steady hiring volume, and recruiters spending too much time on repetitive administrative work instead of candidate and client relationships.

The company context

The reported case describes a mid-sized professional services firm with about 200 employees, multiple locations, and roughly 30-40 open roles per month. The operational friction was concentrated in recruiting and related back-office work.

The operational drag

Recruiters were manually parsing resumes, scanning candidates, coordinating interviews across time zones, sending repetitive follow-ups, maintaining compliance steps, and building weekly recruitment reports in spreadsheets.

What changed

  • Automated resume parsing into structured candidate fields.
  • AI-assisted shortlisting against role criteria.
  • Self-booked interview scheduling with automated reminders.
  • Triggered email sequences for acknowledgments, reminders, offers, and rejections.
  • Real-time dashboards replacing manual weekly reporting.
80-100hours recovered per month
28 -> 19days reported time-to-fill improvement
75%reported reduction in data-entry and scheduling errors

Why it matters for 30-300 employee companies

Recruiting is only one example. The broader lesson is that repeatable intake, scoring, scheduling, communication, and reporting workflows can usually be redesigned before the company adds more headcount. AI is useful when it sits inside a workflow with rules, review points, and clear operational metrics.

Based on a public HireGen reported case study. This page is an internal summary written for The Neural Agency's buyer education.

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