Hire faster with AI-ranked talent
Describe the role in plain language. RecruitZ searches GitHub, LinkedIn, Indeed and Naukri, then ranks every match with the reasons behind it.
Aarav Menon
Senior ML Engineer · 5 yrs
Bengaluru, India
- Evidence for Python, PyTorch, LLM, RAG
- Based in requested location
- Active in the last 30 days
Illustrative result. Not a real person.
Searches connected and publicly available talent sources
From requirement to ranked shortlist
This is what a recruiter sees after submitting a requirement: ranked candidates, the evidence behind each score, and where every profile came from.
Demo screen with made-up people and numbers. Real results come from the sources you select.
RecruitZ doesn't just find candidates. It shows you why they match.
- Every requirement is checked separatelySkills, location and experience each show what was found, what is only partial, and what was not found.
- Match and confidence are differentA high match with thin evidence is flagged. Confidence reflects how much real evidence exists.
- Nothing is inventedIf a source has no evidence, RecruitZ says so. It never fills gaps with guesses.
Why this candidate?
Illustrative result- Evidence found
Python
Primary language in 14 repos · Seen in repo ml-pipeline +3 more
- Evidence found
PyTorch
Seen in repo vision-models +1 more · Mentioned in bio
- Partial evidence
LLM
Mentioned in bio (no project evidence found)
- Evidence found
Location
Bengaluru fits the requested locations
- Not found
Kubernetes
Not found in available evidence
Match
86%
Confidence
High
"Not found" means no evidence was available. It does not mean the person lacks the skill.
From a one-line brief to a ranked shortlist
Describe the role
Write the brief the way you would say it. AI extracts role, skills, experience and locations.
Search your sources
Pick GitHub, LinkedIn, Indeed and Naukri in any mix. Every connected source is searched at once.
Review ranked matches
Each candidate gets a transparent score, the reasons behind it and public contact details.
Built for recruiters who need to trust the shortlist
Evidence-based scoring
Skills, relevance, location, experience and activity are scored separately, so you always see why a candidate ranks where they do.
One ranking, many sources
Results from every selected source are merged and scored on the same scale.
Plain-language briefs
No boolean strings or filter forms. Paste a job line and edit the structured result.
Live results
Candidates stream in as they are analyzed. Start reviewing before the search ends.
Private by design
Briefs are parsed by a local model. Contact details show only when people published them.
Where candidates come from
Every candidate shows its source. Select the sources you want for each search. Results from all of them are scored on one scale.
GitHub
Official GitHub API
Developers and their public repositories, checked for real skill evidence.
Public profile pages, found by web search
Public profile snippets. RecruitZ does not use LinkedIn's API or sign in to LinkedIn.
Portfolios
Public personal websites
Personal sites that are read for published email, location and resume.
Indeed
Connect your API
Available once an API connection is added.
Naukri
Connect your API
Available once an API connection is added.
Built to be used responsibly
Public information only
RecruitZ reads what people have published publicly. It does not sign in to other sites or get past a login.
Self-published contact details
An email or phone number is shown only when the person put it on their own public profile or site, with where it was found.
Briefs stay local
Hiring requirements are understood by an AI model running on your own server, not sent to an AI provider.
Sign-in required
Only authorized users can search. Sessions are not stored in the browser.
Audit trail
Searches, exports and outreach drafts are recorded in an audit log.
Evidence, not guesses
Scores come with their evidence, and missing evidence is shown as missing.
Ready to find your next hire?
Turn a hiring requirement into an evidence-backed shortlist.