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Vena Medical
Case Study

From 500 Unfiltered Applications to a Structured Shortlist - and a Hire

The last time Vena Medical posted a role on Indeed, 500 applications landed in 3 days and none were reviewed. This time, Virvell screened 123 candidates through structured AI pre-screens, completing 78 evaluations with reports in 26 seconds each. Three candidates were shortlisted, interviewed, and one was hired - with zero client hours spent on screening.

123
Candidates Screened
78
Completed Pre-Screens
50 in 3hrs
Peak Screening Speed
5
Simultaneous Screens
3
Shortlisted
1
Hired
The Client
CompanyVena Medical Holdings Corp.
IndustryMedical Devices - Intravascular Imaging & Catheter Technology
Company Size~17 employees (Y Combinator W18)
LocationKitchener, Ontario (Medical Innovation Xchange)
Role HiredR&D and Manufacturing Catheter Assembler
Virvell ModulesAI Pre-Screen Interviews + Background Verification
Recent MilestonesFDA clearance, $4.5M Manufacturing Centre of Excellence, 100+ patients treated
The Challenge
500 Applications, Zero Bandwidth

Vena Medical was at an inflection point. They had just received FDA clearance for their MicroAngioscope System - the world's smallest intravascular camera - opened a $4.5M Manufacturing Centre of Excellence, and were preparing to enter the U.S. market. Ontario's Minister of Economic Development cut the ribbon at their new facility.

To scale production, they needed to hire a specialized R&D and Manufacturing Catheter Assembler - someone with cleanroom experience, GMP documentation skills, and ideally hands-on catheter assembly background. It's a niche role in a competitive corridor (Kitchener-Waterloo) alongside employers like Baylis Medical, StarFish Medical, and Medtronic.

They'd tried this before - and it didn't work. CEO Michael Phillips described what happened the last time they posted on Indeed: within three days, 500 applications flooded in, and there was no way to filter them. With no HR department, no recruiter, and two engineer-founders juggling FDA submissions and manufacturing setup, the applications sat unreviewed.

This time, when the posting went live across Dover, Indeed, and LinkedIn, 123 applications arrived within days. But this time, they had Virvell.

The core problem:

500 applications sat unreviewed last time. 123 new applications arrived this time. A 17-person medtech startup with no HR function needed a way to screen every applicant consistently for a highly specialized manufacturing role - without pulling engineer-founders away from FDA clearance and U.S. market entry.

The Solution
What Virvell Did

Through a consulting engagement via the Medical Innovation Xchange (MIX), Virvell deployed its AI-powered screening platform to handle the entire pre-screening process for Vena Medical's catheter assembler hire.

1

Built a Bill 149-Compliant Job Posting

Ontario's Working for Workers Act requires AI disclosure, pay transparency, and vacancy status on all job postings. Virvell ensured the Dover careers page and Indeed posting included all required disclosures from day one - including the explicit statement that AI assists in screening while a human reviewer makes all hiring decisions.

2

Configured Role-Specific AI Pre-Screening

The platform was configured with 12 custom pre-screening questions tailored to the catheter assembler role: cleanroom experience (ISO class), GMP documentation familiarity, catheter/guide wire assembly background, microscope and precision work, and availability/compensation alignment. Every candidate received the same structured evaluation - no variance between calls, no interviewer bias.

3

Screened 123 Candidates via Voice AI

Rather than cherry-picking resumes, Virvell ran AI-powered voice pre-screens on all 123 applicants. The platform called candidates directly and left voicemails for those who didn't answer, with a callback code so they could complete their pre-screen on their own time. Calls were available 24/7 - and candidates took advantage of it, with 55 calling back on their own schedule, many after 9pm.

4

Delivered Structured Reports in 26 Seconds

Each completed pre-screen automatically generated a structured report with the candidate's responses, skills verification, red flag detection, and an AI recommendation (proceed, review, or hold). Reports were generated in an average of 26 seconds after each call. 100% report generation rate - no manual follow-up required.

The Results
78 Screens. One Day. Zero Client Hours.
MetricResult
Total Applications123
Pre-Screens Completed78 (63%)
Screened in First 3 Hours50 candidates
Peak Hour (9-10pm EST)25 completions
Peak Simultaneous Calls5 at once
AI Recommendation: Proceed5 (6%)
AI Recommendation: Review43 (55%)
AI Recommendation: Hold32 (41%)
Inbound Callbacks55 (43% of all calls)
After-Hours Inbound (6pm+)27 candidates
Reports Generated78/78 (100%)
Avg Report Generation Time26 seconds
Shortlisted for Interview3
Hire MadeYes
Client Hours Screening0
How the AI Differentiated Candidates

The AI wasn't sorting randomly. Candidates who lacked the required experience couldn't answer the technical questions - the screening was self-selecting.

Proceed (5)
6.4 avg skills verified
0.8 avg red flags
11 of 12 questions answered
Review (43)
4.4 avg skills verified
3.1 avg red flags
10.5 of 12 questions answered
Hold (32)
1.7 avg skills verified
2.9 avg red flags
5.9 of 12 questions answered

"Proceed" candidates averaged 6.4 verified skills and answered nearly every question. "Hold" candidates averaged just 1.7 skills and couldn't answer half the technical questions - because they didn't have the experience. The AI detected the difference.

The Timeline
One Day, 78 Screens

On March 11, 2026, Virvell began screening candidates at 12:30pm EST. Outbound calls reached all 123 candidates throughout the afternoon. By 11:30pm that same day, 50 pre-screens were completed - with candidates continuing to call back through the evening and into the night. Callbacks continued for five more days, including weekends, ultimately reaching 78 completed screens. A human recruiter conducting 20-minute phone screens could handle about 15 in a full workday. Virvell completed 50 on day one alone.

The screening timeline:
12:30pm - Outbound calls begin reaching all 123 candidates
5:00pm - All candidates contacted. First completions arriving.
9:00pm - 21 completed. Inbound callbacks accelerate as candidates call back after work.
9:30pm - 33 completed. Peak: 25 completions in one hour, up to 5 simultaneously.
11:30pm - 50 completed. Candidates still calling back past midnight.
Days 2-5: Callbacks continued through Thursday, Friday, Saturday, Sunday, and Monday - reaching 78 total.
Candidates Called Back After Hours

Of the 123 candidates, 55 chose to call back on their own time rather than answering the initial outbound call - 43% of all completed screens were candidate-initiated. Twenty-seven of those inbound callbacks happened after 6pm, with candidates who received an outbound call or voicemail during the afternoon calling back hours later, at 9pm, 10pm, 11pm, even past midnight. These are manufacturing workers calling after their shift, after dinner, after putting their kids to bed. No recruiter is available to take those calls. The AI was.

Traditional With Virvell
Time to screen 1233-4 weeksOne day + callbacks
Client hours30-40+0
ConsistencyVaries by call100% standardized
After-hoursNone (9-5)24/7 (55 callbacks)
Simultaneous1 at a time5 at once
Bill 149Manual effortBuilt-in
ComparisonNotes / memorySide-by-side reports
Report speedHours / never26 seconds
The Outcome
From 123 Applicants to 1 Hire

From 123 applicants, Virvell's AI pre-screening identified 5 "proceed" candidates and 43 for "review." Vena Medical's founders selected three finalists for on-site interviews and dexterity testing - drawn from both the proceed and review tiers, validating the human-in-the-loop model. The AI didn't make the decision. It organized the information so the founders could.

Two of the three finalists came from the "review" tier, not just "proceed." The founders looked at the full AI reports, weighed the verified skills against the flagged gaps, and decided those candidates were worth meeting in person. That's the system working as designed: AI collects data, humans decide.

The hire:

Vena Medical made the hire. The successful candidate had received a "proceed" recommendation from the AI, with the highest number of verified skills and the fewest red flags of any candidate screened.

Cross-Module Intelligence: Two Sources, One Consistent Picture

After the hiring decision was made, Virvell ran a background check on the successful candidate through its integrated Certn partnership. The background check returned clear with no criminal records. Virvell's cross-module intelligence engine then automatically compared data from the pre-screen conversation against the background verification results.

The result: high consistency across both modules. Four facts stated during the AI pre-screen were independently verified, with zero discrepancies detected between sources. One item was flagged for the hiring team's consideration, with a specific recommendation for follow-up during onboarding.

This is the platform working as designed. Pre-screen data and background verification feeding into a single intelligence layer that surfaces what aligns, what doesn't, and what needs a closer look. No single-service competitor can do this because they only see one data source.

Cross-module results for the hired candidate:

4 verified facts confirmed across sources. 0 discrepancies detected. 1 item flagged for human review. Background check: all clear. Two independent data sources, one consistent picture.

123 applied > 78 screened by AI > 5 proceed + 43 review > 3 interviewed > 1 hired

Total time from job posting to hire: approximately 3 weeks. Client screening time: zero.

"We tried posting this job on Indeed, and we got, within three days, 500 applications. And I couldn't filter through them... it was just impossible."
Michael Phillips, CEO, Vena Medical
"Interviewing and hiring is a skill, one which I think we're still learning. It's a fair amount of mindshare managing interviews and the flow of everyone."
Phillip Cooper, COO, Vena Medical
Why This Matters

Vena Medical's story isn't unique. Across Canada, high-growth startups face the same dilemma: they post a role, get flooded with hundreds of applications, and have no way to process them. The default is the founder doing phone screens between investor calls and product launches - or, as Vena experienced firsthand, 500 applications sitting unreviewed because nobody had the bandwidth to filter them.

Virvell changes that equation. By combining AI pre-screen interviews, background verification, and voice AI reference checks into a single platform, companies like Vena Medical get enterprise-grade screening without needing an enterprise-sized team.

Key Takeaways
123 candidates screened, 78 completed, 1 hired - complete funnel from application to offer
50 pre-screens completed on day one. A task that would take a recruiter 3-4 weeks.
55 candidates called back on their own time - at 9pm, 10pm, 11pm, even weekends
The candidate who was hired had received a "proceed" recommendation from the AI
Two "review" candidates made the final three - proving human-in-the-loop works
Cross-module intelligence confirmed high consistency across pre-screen and background check - zero discrepancies
Bill 149 compliance built into the workflow, not bolted on after
AI collects data, humans decide - no candidate scoring, no auto-rejection

About Vena Medical

Vena Medical Holdings Corp. builds the world's smallest intravascular cameras, giving physicians a live view from inside blood vessels. Founded as a University of Waterloo capstone project in 2016 and backed by Y Combinator (W18), Vena Medical has treated 100+ patients across Canadian hospitals, holds 9 granted patents, and recently received their first FDA clearance for peripheral vascular use. They are headquartered in Kitchener, Ontario at the Medical Innovation Xchange.

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