Evidence-backed fit

AI Candidate Matching With Evidence.

Add role criteria, profile evidence and open questions to a search brief. Yena organises the visible signals; recruiters review sources and decide what to investigate before outreach.

Evidence-backed fitBeyond BooleanReviewable matching signals
Senior Python Developer
Python Developer
Role and skill signal
Review
Backend Engineer
Related experience signal
Review
ML Engineer
Technology context signal
Review

Illustrative example, not a real search result

Context
for a structured search review
Evidence
to inspect before outreach
Human
review remains the next step

Make a search brief reviewable.

A title alone rarely captures a role. Add skills, experience and open questions, then review the visible signals before deciding what to investigate next.

Keyword search: illustrative example
Search: 'Senior Python Developer'

Finds: profiles containing the entered terms

  • Also review: 'Backend Engineer' (Python stack)
  • Also review: 'Data Engineer' (Python pipelines)
  • Also review: 'ML Engineer' (TensorFlow = Python)

Review question: which relevant context is missing?

✅ AI Semantic Matching
Search: 'Senior Python Developer'

Finds: entered terms and related signals to review

  • + 'Backend Engineer' (Python-heavy)
  • + 'Data Engineer' (Python data work)
  • + 'ML Engineer' (Python ML frameworks)

Result: context signals support human review

How AI Semantic Matching Works.

Yena connects role context with visible signals. Recruiters review the interpretation and decide what happens next.

Job Title Variations

Groups related job titles and seniority terms as signals for review. The brief and recruiter determine the concrete fit.

Search 'Senior Engineer' can surface related titles

Skill Context & Tech Stacks

'Python' includes Django (web), Pandas (data), TensorFlow (ML), Ansible (DevOps)—different contexts for different roles.

Search 'Backend Python' prioritizes Django/Flask

Industry-Specific Expertise

Adds industry and practice context as signals without deciding professional eligibility automatically.

Search 'Primary Care' makes context visible

Experience Level Nuance

Considers experience scope and responsibility. Recruiters check whether the evidence fits the specific brief.

Search for plant leadership includes responsibility scope

Practice Specialization

Can surface specialisations and project signals in the context of a request; the recruiting team makes the professional selection.

Search for M&A experience makes project signals visible

Human review

Work with the available profile and search signals. Check results for freshness, purpose and unresolved questions.

Add a new term when the brief or market context requires it

Illustrative Examples.

Healthcare: 'Primary Care Physician'

Search briefing:

The setting, care focus and exclusions need to be agreed for the assignment.

Yena context signals:

  • Shows: possible profiles and the visible signals behind them
  • Review question: does the practice setting fit the brief?

Illustrative briefing: recruiters review context and sources

Legal: 'M&A Tax Attorney'

Search briefing:

A title alone does not show which transaction experience the assignment requires.

Yena context signals:

  • Shows: possible tax profiles with visible project signals
  • Project signals: experience with M&A transactions

Illustrative comparison: recruiters review transaction type and evidence

Manufacturing: 'Plant Manager with Industry 4.0'

Search briefing:

An industry term can be too broad without project and responsibility evidence.

Yena context signals:

  • Signals: led smart-factory and digitalisation projects
  • Technology: IoT sensors, MES, digital twin

Illustrative comparison: recruiters review projects, signals and technology context

Reviewable workflow

Review signals before outreach

Yena helps organise search signals. Recruiters check sources, freshness and fit before deciding the next step.