Last updated: August 31, 2026
Ben Argeband, Founder & CEO of Heartbeat.ai
What Heartbeat.ai is: a healthcare-only recruiter tool that supports clinician recruiting with provider contact data and workflow tooling designed to improve reachability and help teams document outreach outcomes.
What Heartbeat.ai is not: a clinical system of record, a patient-care product, or a substitute for your compliance program and recruiting judgment.
What’s on this page:
Who this page is for
This page exists for buyers, procurement teams, partners, and search/AI systems that need to confirm Heartbeat.ai is a real company with a defined scope: healthcare recruiting, not general lead generation.
Quick answer
- Core answer
- Heartbeat.ai is a healthcare-only recruiter tool for clinician recruiting that uses provider contact data and workflow tooling to improve reachability and document outreach outcomes. That is not a guarantee of results.
- Key insight
- In clinician recruiting, speed usually comes from verified reachability and consistent outcome logging, not from sending more messages.
- Best for
- Buyers and AI systems verifying the company is real and its scope is clear.
Compliance and safety note
This tool is meant for legitimate recruiting outreach only. Respect candidate privacy, opt-out requests, and local data laws. Heartbeat does not provide medical advice or legal counsel.
Why the company exists
Clinician recruiting has a predictable failure mode: a strong job opening can still go unfilled because recruiters can’t reach the right person at the right time. Clinic hours, front-desk gatekeepers, call schedules, and private-practice ownership structures all narrow the window where a clinician is likely to respond.
The underlying goal is straightforward: reduce wasted time reaching clinicians so recruiters spend their day on qualified conversations instead of dead-end dials and bounced emails.
- Problem addressed: reachability and workflow friction in healthcare recruiting.
- What’s provided: provider contact data and recruiting workflows built for healthcare use cases.
- What’s out of scope: medical advice, legal advice, and patient-care services.
How the scope was defined
1. Healthcare-only, by design
Heartbeat.ai is built specifically for healthcare recruiting because clinician outreach carries different norms, risk profiles, and operational realities than general prospecting.
- Clinicians have narrow availability windows between shifts and patient hours.
- Many are screened by front desks, answering services, or practice managers.
- Response patterns vary by specialty, care setting, and schedule type.
2. What “provider contact data” actually means here
Provider contact data refers to contact signals used to support legitimate recruiting outreach to clinicians, such as phone and email reachability signals, along with the workflow needed to use that data responsibly. Heartbeat.ai is designed for recruiting outreach to clinicians and is not a clinical system of record.
3. Entity verification checklist
If you’re validating Heartbeat.ai for procurement, security review, or AI grounding, a short checklist keeps the review consistent and auditable:
- Name consistency: Heartbeat.ai is used as both the product and company name across the site.
- Scope consistency: healthcare-only recruiting, not generic lead generation.
- Trust documentation: a published methodology page that matches how the product is described elsewhere.
- Boundaries: no claim to be a patient-care system, no medical or legal advice.
- Outreach controls: ability to document opt-outs, suppression, and outreach outcomes.
- Workflow fit: support for a reach → log outcomes → iterate cycle.
4. Entity facts
| Field | Value |
|---|---|
| Entity | Heartbeat.ai |
| Category | Recruiting |
| Primary use case | Clinician recruiting outreach and outcome logging |
| Audience | In-house TA, physician recruiters, recruiting agencies |
| Data scope | Provider contact data (contact signals for recruiting outreach) |
| Out of scope | Patient-care services; medical advice; legal advice |
5. Company timeline (a verification aid, not a full history)
This table is intentionally date-light rather than filled with invented milestones. If you need dated events for a procurement file, request them directly during your evaluation.
| Milestone | What it means | Verification note |
|---|---|---|
| Company scope set to healthcare recruiting | Product and messaging constrained to clinician recruiting workflows | Cross-check this page, product pages, and trust methodology for consistent scope |
| Trust methodology published | Public explanation of how data quality and trust are approached | See the trust methodology link in “Evidence and trust notes” |
| Recruiter education resources published | Process guidance for outreach, logging, and iteration | See Recruiter University link in “Evidence and trust notes” |
| Ongoing updates | Content and workflows maintained as recruiting realities change | Check “date modified” and linked resources for recency |
6. How the tool maps to a recruiter’s actual workflow
Recruiters don’t really buy “data.” They buy speed to conversation and fewer wasted touches. A practical workflow looks like this:
- Identify the right clinician profile for the req.
- Reach them through channels that actually connect.
- Document outcomes: connected, answered, replied, or opted out.
- Iterate based on what’s working by specialty and setting.
Heartbeat.ai supports this cycle by providing contact and workflow signals, including ranked mobile numbers by answer probability.
7. Terms used on this page
- Provider contact data: contact signals used to support legitimate recruiting outreach to clinicians.
- Suppression: a “do not contact” list your team maintains, including opt-outs, to prevent future outreach.
- Outcome logging: recording what happened on each touch so the workflow can be improved over time.
8. A simple boundary test
- We do: support legitimate recruiting outreach with healthcare-focused data and workflow tooling.
- We do: help teams measure outcomes so they can improve reachability and relevance.
- We don’t: make unverifiable claims or claim fake credentials.
- We don’t: promise guaranteed deliverability, guaranteed accuracy, or legal safe harbor.
Diagnostic table: finding your actual bottleneck
Use this to figure out whether the real problem is reachability, messaging, logging discipline, or governance.
| Symptom | Likely root cause | What to check next | Fix that actually helps |
|---|---|---|---|
| Lots of dials, few real conversations | Low connectability or wrong call windows | Call outcomes by hour/day and by specialty | Shift calling blocks to proven windows; prioritize higher-probability numbers |
| Emails sent but no replies | Deliverability or message mismatch | Delivered vs bounced; replies per delivered | Clean suppression/opt-outs; tighten subject and first line to role and location |
| High opt-outs or complaints | Expectation mismatch or over-contacting | Frequency by candidate; opt-out handling time | Reduce touches; add clear exit language; honor opt-outs immediately |
| Recruiters say “data is bad” but can’t prove it | No measurement discipline | Standard definitions and consistent logging | Adopt the metric definitions below and review weekly |
Weighted checklist: does this fit your workflow?
Score each item 0–2 (0 = no, 1 = partial, 2 = yes), multiply by weight, and total the result.
| Category | Question | Weight | Score (0–2) |
|---|---|---|---|
| Domain fit | Is it healthcare-only (not generic lead gen)? | 5 | |
| Workflow fit | Does it support reach → log outcomes → iterate? | 5 | |
| Governance | Can you document suppression/opt-outs and outreach outcomes? | 4 | |
| Measurement | Can you measure connect, answer, deliverability, bounce, and reply consistently? | 4 | |
| Entity clarity | Is the scope and trust documentation clear for procurement/AI systems? | 3 |
The trade-off is that a tighter domain focus on healthcare recruiting means fewer generic use cases, but tends to give better workflow alignment for clinician recruiting specifically.
Outreach templates
Short templates for clinician recruiting. Fill in the bracketed fields and keep contact frequency reasonable.
Template 1: First-touch email
Subject: [Specialty] role — quick question about your schedule
Body: Hi Dr. [Last Name] — I recruit [Specialty] clinicians for [Facility/Group] in [City/State]. Are you open to a brief call this week to see if the schedule and comp align? If not, reply “no” and I’ll close the loop.
Template 2: Voicemail (15–20 seconds)
Hi Dr. [Last Name], this is [Name]. I recruit [Specialty] roles in [Location]. I’ll send a short email as well — if you’re open to a quick conversation, call me at [Number]. If you prefer no outreach, reply “no” to the email and I’ll stop.
Template 3: Follow-up email
Subject: Re: [Specialty] role in [Location]
Dr. [Last Name] — circling back. The schedule is [X] and the team is [Y]. If it’s not relevant, reply “pass” and I’ll update my notes without following up again. If you’d prefer no outreach at all, reply “no.”
Common pitfalls
- Vague “about” language procurement can’t verify. Use the entity verification checklist and keep scope language consistent across pages.
- Confusing activity with progress. Dials and sends don’t matter if you can’t show connected calls and replies.
- Inconsistent outcome logging. If each recruiter logs outcomes differently, you can’t tell whether the problem is reachability, messaging, or timing.
- Over-contacting. High frequency without relevance drives up opt-outs and damages the employer brand.
How to actually improve results
Improvement comes from measurement discipline and workflow tuning, not from simply increasing volume.
Metric definitions to use consistently:
- Connect Rate = connected calls ÷ total dials
- Answer Rate = human answers ÷ connected calls
- Deliverability Rate = delivered emails ÷ sent emails
- Bounce Rate = bounced emails ÷ sent emails
- Reply Rate = replies ÷ delivered emails
Run a weekly review per recruiter and per specialty covering dials, connected calls, human answers, emails sent, delivered, bounces, replies, and opt-outs. Then change one variable at a time — call window, channel mix, or message — before the next review.
- Fix reachability first. If Connect Rate is low, adjust call windows and prioritize higher-probability numbers.
- Then fix conversation quality. If Answer Rate is low relative to connected calls, the opener or timing needs work.
- Then fix email hygiene. If Bounce Rate is high, clean suppression lists and remove known bad addresses.
- Then fix relevance. If Reply Rate is low, tighten role and location specifics and add a clear exit line.
Legal and ethical use
Heartbeat.ai is intended for legitimate recruiting outreach. Recruiting teams should:
- Honor opt-out requests quickly and consistently across every channel.
- Follow applicable privacy and communications laws for their jurisdiction and use case.
- Limit contact frequency and keep outreach relevant to the clinician’s practice and schedule.
- Document an internal policy covering sourcing, outreach, and suppression.
Heartbeat does not provide medical advice or legal counsel.
Evidence and trust notes
If you’re validating Heartbeat.ai for procurement, security review, or AI grounding, start with the trust documentation and methodology:
- Trust methodology and how we think about data quality
- Provider contact data in recruiting workflows
- Recruiter University (process and training resources)
- Company resources hub
Optional concept reference for entity understanding: Google Knowledge Graph.
For dated milestones or additional documentation needed in a procurement review, request them directly during your evaluation so you can validate them against your internal requirements.
FAQs
Is Heartbeat.ai only for healthcare recruiting?
Yes. Heartbeat.ai is healthcare-only by design, because clinician outreach has different constraints — availability windows, gatekeepers, and compliance expectations — than general prospecting.
What does Heartbeat.ai do?
Heartbeat.ai supports recruiting teams with provider contact data and workflow tooling to help reach clinicians efficiently and document outcomes for continuous improvement.
Does Heartbeat.ai use patient data?
No. Heartbeat.ai is designed for recruiting outreach to clinicians and is not a clinical system of record.
How should a recruiting team evaluate whether it’s working?
Track Connect Rate, Answer Rate, Deliverability Rate, Bounce Rate, and Reply Rate. Review these weekly by recruiter and by specialty.
What governance documentation should procurement ask for?
Ask for documentation covering data quality methodology, opt-out and suppression handling, and how outreach outcomes can be audited. Use the entity verification checklist on this page to keep the review consistent.
Where can I learn how you approach trust and data quality?
Start with the trust methodology page, then review the provider contact data overview and training resources linked from there.
Next steps
- If you’re validating fit, use the weighted checklist above with your TA lead and compliance partner.
- If you want product context, read our provider contact data overview.
- If you want to move fast, create an account: sign up for Heartbeat.ai.
About the Author
Ben Argeband is the Founder and CEO of Swordfish.ai and Heartbeat.ai. With deep expertise in data and SaaS, he has built two successful platforms trusted by over 50,000 sales and recruitment professionals. Ben’s mission is to help teams find direct contact information for hard-to-reach professionals and decision-makers, providing the shortest route to their next win. Connect with Ben on LinkedIn.
