Case Study

Applicant Intake & Re-Engagement at Production Scale

Regional Rainbow Vacuum Distributor · Tier 3 Production System

Client
Regional Rainbow vacuum distributor (anonymized)
Project
Applicant intake & re-engagement pipeline (Tier 3 production)
Stack
n8n on hardened VPS · Postgres · Google Sheets · Gmail API
Role
System design and production deployment
Outcome
Production system live; 10,580 applicants processed at 100% classification across 8.5-month batch; 3,113 candidates in review queue

The Situation

A regional Rainbow Vacuum Distributor was losing hiring opportunities every day — not because applicants weren't applying, but because the team couldn't keep up with them.

Applicant data sat unreviewed in spreadsheets. Follow-up depended on whoever had time to send a text. Nobody had a clear picture of who had been contacted, who had replied, or who had already moved on. The pipeline wasn't moving because the manual layer between "applicant applies" and "applicant gets contacted" was the bottleneck.

Every day of delay was a candidate lost to a competitor or to silence.


The Real Problem

This wasn't a hiring volume problem. The applicants were there.

The business was losing candidates between intake and first contact — a gap that no amount of job posting spend could fix. The pipeline needed to move on its own, without depending on manual bandwidth that was already maxed out.


The System Brealle Built

Regional Rainbow Vacuum Distributor Applicant Pipeline v5 PROD — a three-chain automation that runs continuously on a hardened production VPS, processing incoming applicant records from raw intake through outreach, reply tracking, and pipeline state management.


System Architecture

Chain A — Intake & Qualification

Pulls raw applicant rows from the intake sheet, dedupes against the master pipeline using generated keys, normalizes fields, applies decision logic, and writes both to the master pipeline and to a human-review queue. Duplicates aren't silently dropped — they're routed through a dedicated logging branch and recorded before the chain merges back to the main path.

Chain B — Outreach (Re-Engagement)

Pulls approved candidates from the review queue, builds personalized re-engagement emails, enforces a daily send cap so the system never exceeds Gmail throughput limits, sends through Gmail with 3-minute pacing between messages, captures the thread ID for downstream reply matching, and logs every send.

Chain C — Reply Handling

Runs on a 15-minute schedule. Pulls active threads from the pipeline, fetches new replies from Gmail by thread ID, matches each reply back to the original candidate, decides whether to respond, sends a threaded reply (also under daily cap), updates pipeline stage and review queue, and logs the chain.

Error Subworkflow — Failure Logging & Halt Handling

Built-in error trigger subworkflow. Any failure in any chain routes to a structured error log entry with chain identifier, timestamp, and error context.


Operational Controls

These are the controls that distinguish a production system from a demo:


Results — Production Outcomes

Directly observed metrics from the most recent production batch:

10,580
Applicants processed in 8.5-month batch
100%
Classification rate
71%
Auto-filtered out-of-territory before reaching the operator's queue
8.5 mo
Historical batch range covered in a single session
Tier 3
Production governance class

Governance

The system is governed under Brealle's Workflow Governance Standard (WGS) v1 at Tier 3 — Brealle's highest-risk workflow category, used for external communications with low reversibility.

Tier 3 controls applied:


Production Footprint

Layer Implementation
Orchestration n8n on hardened VPS
Reverse proxy + TLS Caddy with managed TLS
State Postgres-backed n8n instance
Hardening Hardened Linux server, key-based access, firewall enforced

What This Replaces

What's Now Possible


Key Insight

The constraint was never applicant volume.
It was the manual layer between intake and engagement.

Positioning Statement

Most hiring pipelines don't fail because of bad candidates. They fail because the gap between application and first contact is too slow, too manual, and too dependent on someone remembering to follow up.

Brealle builds the system that closes that gap — so the pipeline runs whether or not someone is working the queue that day.


About Brealle

Brealle designs and operates production automation systems for businesses where revenue depends on inbound capture, intake, follow-up, and tracking.

Ready to find where your pipeline is leaking? Start with a Lead Loss Snapshot.

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Brandon Robinson
Founder, Brealle