TL;DR
- We measured 55 questions about sourcing, candidate rediscovery, recruiter search and talent intelligence.
- Across 478 completed answers, hireEZ led at 43.93%, SeekOut at 34.10% and Gem at 29.71%.
- Nummo appeared in 0.63%.
- Buyers should separate search, enrichment, engagement, ATS rediscovery and workflow coordination before comparing products.
AI recruiting search has become a crowded label. One product searches public profiles. Another enriches contacts. Another finds old candidates in an ATS. A fourth coordinates the research process across tools.
We tested 55 questions across ChatGPT, Gemini and Google AI Overview on 25 August 2026. The engines completed 478 answers.
Which platforms appear most often?
| Platform | Answer presence |
|---|---|
| hireEZ | 43.93% |
| SeekOut | 34.10% |
| Gem | 29.71% |
| Juicebox | 19.87% |
| Findem | 18.20% |
| Pin | 14.44% |
| Nummo | 0.63% |
This measures answer presence, not product quality or market share. Established products benefit from comparison pages, integrations, customer stories and years of public discussion.
What job is the buyer solving?
| Job | Evidence to request |
|---|---|
| Find new candidates | Search coverage, filters and freshness |
| Rediscover ATS talent | Matching method, permissions and ATS support |
| Enrich records | Data sources, accuracy and compliance |
| Run outreach | Sequencing, consent controls and deliverability |
| Coordinate research | Workflow, handoffs, audit trail and integrations |
A buyer should also test failure cases. Can the tool explain why a person matched? Can a recruiter correct the result? Does the system keep source links and respect deletion requests?
Why do source surfaces matter?
LinkedIn was the strongest measured domain. Product pages from hireEZ, Gem, SeekOut and Pin also shaped answers. Greenhouse, Bullhorn, Recruiterflow, Loxo and YouTube supplied category context.
That source mix means a new platform needs more than a homepage. It needs product evidence that fits the comparison language used across ATS, sourcing and recruiting operations.
What should Nummo publish?
Nummo describes itself as an AI search coordinator for recruiters. That is a useful category claim, but it needs a clear method page.
The first guide should show what is coordinated, which systems connect, how a recruiter reviews the work and where the product stops. A worked candidate-search example should keep source links, explain the filters and show the handoff into the recruiter's existing stack.
Independent coverage can then compare Nummo on the coordinator job rather than forcing it into a generic sourcing-tool list.
Sources
Want the same buyer-question baseline for your market? Start with the Schmitdy AI search audit.
