All Case Studies
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🎯 Technical Recruiting · Austin, TX · 6-Person Agency · Bullhorn CRM
Candidate Intelligence · Semantic Matching · Outreach Automation

6 People Beating a 30-Person Competitor.
The First to Present Wins.

A 6-person boutique was losing 30–40% of placements purely on speed. We built a candidate intelligence platform that cut time-to-present from 5.2 days to 1.6 — and nearly doubled revenue per recruiter.

5.2d
Before
→
1.6d
After
1.6 days
Time-to-present — was 5.2 days
22–28%
Response rate — was 8–12%
3.8×
Placements per recruiter/month — was 2.1
~$34K
Revenue per recruiter/month — was ~$18K
Retained
Institutional knowledge — no longer walks out the door
Industry
Tech Recruiting
Team Size
6 recruiters
Location
Austin, TX
CRM
Bullhorn · 45K records
Engagement
4 weeks
Focus
SWE · DevOps · Data
The Problem

Not Losing on Quality.
Losing on Speed.

By the time they presented candidates, the client had already committed to the larger competitor.

Time-to-present — who wins the placement
30-person competitor
1.8d
→ interviews scheduled first
Before
5.2d
→ client already committed
After
1.6d
✓ presents first, wins placement
🔑
Keyword Search Missed 40% of Matches
~40% of valid candidates never surfaced
📧
Generic Outreach Got Ignored
8–12% response rate · hours to write
🚪
Knowledge Walked Out With Recruiters
4 years of signals — lost entirely
30–40%
Placements lost to speed
3–4 hrs
Manual sourcing per job order
8–12%
Outreach response rate
2.1×
Placements/recruiter/month
Platform Architecture

Match. Explain. Outreach. Remember.

Automating the information retrieval that consumed 60% of each recruiter's day.

🔍 Semantic Matching Engine
Cloud Equivalencies
AWS≈Amazon Web Services
GCP≈AWS transferable
Azure DevOps≈CI/CD competency
IaC / DevOps
Terraform≈Pulumi≈CloudFormation
Kubernetes→implies Docker
Spring Boot→implies Java
Seniority Inference
"Led migration to microservices"
→ Senior / Staff signal
"Participated in microservices dev"
→ Mid-level signal
↓ matched candidates scored against real-time signals
⏱️ Receptivity Timing Signals
2-year mark approaching
Post-vesting cliff
LinkedIn headline change
Resume updated last 30 days
Recent outreach response
Company announced layoffs
↓ four supporting modules
📋
Job Order Intelligence
Extracts requirements, checks prior submissions, surfaces top 15 matches with scores in minutes.
✉️
Personalized Outreach
Context-aware messaging adapting tone per recruiter. Full 3-message sequence drafted for review.
🧠
Knowledge Capture
Every call note, outcome, and preference structured and saved. Persists through recruiter turnover.
💡
Proactive Context
Historical context surfaces automatically before outreach — prior submissions, preferences, compensation.
Job Order → Briefing Pipeline
01
Job Order
Email or Slack
→
02
Parsed
Must-haves · comp · remote
→
03
45K Scanned
Semantic + timing + history
→
04
Top 15 Ranked
Score + explanation each
→
✓
Briefing Ready
Minutes, not 3–4 hours
The Proof

30-Second Decision.
Not 10-Minute Resume Review.

bullhorn-connected · role: senior-devops-eng · 15 candidates evaluated ⚡ 47 min since job order
Senior DevOps Engineer — Series B SaaS · Austin, TX (hybrid)
$165K–$195K · 5+ yrs Kubernetes · Terraform/IaC · CI/CD · AWS required
Kubernetes AWS Terraform CI/CD Prometheus Python scripting
▸ Top Matches — ranked by composite score
MR
Marcus Reid
Sr. Platform Eng · Homeward (Austin) · 2 yrs 1 mo
94
match
✓7 yrs Kubernetes — led cluster migration, runs Helm in prod
✓AWS + Terraform — multi-region infra, active IaC commits
✓CI/CD — GitHub Actions from scratch; prior Jenkins experience
✓Comp range — currently $158K; target $170–180K per CRM note
△Gap: Prometheus — uses Datadog; transferable monitoring exp
✓ 2yr 1mo — typical move window LinkedIn headline updated 12d ago Responded to outreach Feb · positive No prior submissions this client
AT
Anika Thavorn
DevOps Lead · Dell Technologies · 3 yrs 4 mo
81
match
✓K8s + Helm at enterprise scale (50K pods). Terraform 4 yrs. AWS SA certified.
△Gap: comp — last stated $200–220K. Role tops at $195K.
Resume updated 3 days ago — active signal ⚠ Declined via Sarah 8mo ago — see note
✓ Full briefing ready · 15 candidates · review in 35–45 min · job order 47 min ago vs 3–4 hrs before
📧 InMail to Marcus Reid
8% → 24% response
Before — generic
Hi Marcus,

Hope you're doing well! I came across your profile and think you'd be a great fit for an exciting DevOps opportunity with a fast-growing tech company in Austin.

Would you be open to a quick 15-minute call?
After — context-aware
Hi Marcus,

Your K8s cluster migration at Homeward maps directly to what this Series B team needs — rebuilding platform infra from scratch with a similar stack.

The Terraform-first, multi-region approach you run is exactly their model. $170–185K + meaningful equity.

Worth a 15-min call this week?
8–12%
Response · generic
22–28%
Response · personalised
💡 Anika Thavorn — Context Before You Reach Out
⚠
Proactive context — surfaced automatically
Sarah contacted Anika 8 months ago for a similar role. Interested but declined due to below-market comp ($175K offered, wanted $195K+). Was evaluating a Dell internal move.
Source: Bullhorn note · Sarah K. · 8 months ago
📋Nov 2023 — Submitted to Clearbit. Technical pass, declined offer (comp).8 mo ago
📝Dell internal transfer completed. Target comp $200–220K.7 mo ago
📍Hybrid Austin only. Won't relocate.8 mo ago
🔔Resume updated 3 days ago. But comp gap is real: role tops at $195K.3 days ago
🧠 This context was in Sarah's memory. She left 3 months ago. It's now in the platform — available to every recruiter.
First Quarter Outcomes

6 People. 30-Person Competitor.
Presenting Faster. Closing More.

1.6d
Time-to-present
was 5.2 days
3.8×
Placements per recruiter/month
was 2.1
~$34K
Revenue per recruiter/month
was ~$18K
Time to Present
Competitor
1.8 days
Before
5.2 days
After
1.6 days ✓
Outreach Response Rate
Before
8–12%
After
22–28%
Sourcing Time per Role
Before
3–4 hours
After
35–45 min
Semantic Matching Timing Signals Match Explanation AI Outreach Personalization Knowledge Capture Bullhorn ATS/CRM 45K Records Seniority Inference Tech Equivalency Graph LinkedIn Signal Parsing
Metric
Before
After (Q1)
Time-to-present
5.2 days avg
1.6 days avg
Sourcing per role
3–4 hours
35–45 min review
Response rate
8–12%
22–28%
Placements / recruiter
2.1 / month
3.8 / month
Revenue / recruiter
~$18K / month
~$34K / month
Knowledge retention
Lost with recruiter
Systematically captured
The Bottleneck Was Never Judgment
Recruiters still build rapport, negotiate offers, and manage the human side. What changed was the 60% of each day spent on information retrieval — searching, reading, comparing, writing. The platform handles that. Recruiters handle relationships.