InferOwl is an AI operating system for staffing and recruitment. It unifies your ATS, dialer, email, scheduler, document vault, and compliance tracking into a single platform, then wraps an AI agent around every candidate, client, and call to draft outreach, update the pipeline, and coach recruiters.

How is InferOwl different from a traditional ATS like Bullhorn, Ceipal, or JobDiva?

Legacy ATS platforms store data and wait. InferOwl wraps an inference engine around every record, so the system suggests the next best action, automates the busywork, and keeps your pipeline current on its own — with a human approval gate on every action and a full audit trail.

Does the AI agent act without human oversight?

No. Every action — outreach, submittals, follow-ups, credential alerts — is proposed by the agent, reviewed by a recruiter, then executed and logged. Nothing goes out without a human approving it.

Is InferOwl only for healthcare staffing?

InferOwl is a horizontal operating system for staffing and recruitment, proven first in healthcare. Specialty match, licence tracking, shift type, and credential expiry are built into the core data model and extend to IT and other verticals.

How does pricing work?

InferOwl is a per-seat platform plus usage-metered AI — you pay only for the inference you actually use. Book a 20-minute call and we shape a plan around how your team works.

Match candidates to jobs in InferOwl

InferOwl matching ranks available records and explains why a result received its score. Use the ranking to focus review, not as an automated hiring or eligibility decision.

Review and act on matches

01
Start from a job or candidate
Open a job to find candidates, or open a candidate to find jobs, then select the matching action.
02
Run matching
Wait for the ranked results. If matching fails, retry after confirming that the source record contains useful role, specialty, location, experience, and requirement information.
03
Search and filter results
Search within the results or choose a minimum score such as 60, 70, 80, or 90 to narrow the review list.
04
Read why the score was assigned
Open Why this score and compare the explanation with the job requirements, candidate record, source documents, and any known constraints.
05
Record feedback
Mark a result Good match, Needs review, or Not a match when your account has Run matching access. Feedback records user judgment about the result.
06
Shortlist after human review
Shortlist a candidate only after confirming the fit and required information. Shortlisting requires Move candidate stage access.

Keep a person responsible for the decision

A score may reflect incomplete, outdated, or incorrect source data. Recruiters and managers must verify the evidence, apply job-related criteria consistently, and follow applicable employment and anti-discrimination requirements.

Troubleshooting

No matches are returned.

Likely cause: No eligible records meet the current query or the source record lacks useful matching data.

Complete the job or candidate details, remove an overly strict score filter, and run matching again.

The matching request fails.

Likely cause: The service request failed or your account lacks Run matching access.

Confirm your access, retry once, and contact support with the job or candidate ID if the failure continues.

You can review a match but cannot shortlist it.

Likely cause: Shortlisting uses the pipeline-stage permission.

Ask an owner to grant Move candidate stage access or have an authorized teammate complete the shortlist.