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AiRA Search Matrix Your JD, Decoded Into Filters

A keyword search treats every word in your job description the same. The AiRA Search Matrix doesn't. Eva Mendis, your Evaluation Matrix agent, decodes the approved JD into eight weighted filters — so the search knows what actually matters.

Eva reads the signed-off JD line by line, pulls out the attributes that define the role — title, skills, experience, industry, location — and scores each one for relevance. Roadmapping at 95%, Fintech at 92%, SQL / Analytics at 88%. The result is a live search matrix that targets the right people first, and hands the same criteria straight to sourcing and ranking.

How the AiRA Search Matrix Works

From an approved JD to a weighted set of live search filters, in one automated pass:

1

Start from the approved JD

Eva reads the signed-off job description as the single source of truth, so the criteria come straight from what you agreed to hire for — not a fresh search brief.

2

Decode eight attributes

She pulls the role apart into eight fixed attributes — role, skills, education, experience, industry, location, tools and budget fit.

3

Weight what matters

Each attribute gets a relevance score, so a must-have carries more pull than a nice-to-have instead of every keyword counting the same.

4

Build the search matrix

The weighted attributes become live filters — Roadmapping 95%, Fintech 92%, SQL / Analytics 88% — a scored map of the ideal candidate.

5

Target the right people first

Because the matrix is weighted, the closest matches surface first instead of a flat keyword dump you have to triage by hand.

6

Feed sourcing and ranking

The matrix hands off downstream, so sourcing and ranking work from the same criteria — no re-keying requirements at each stage.

Keyword Search vs a Weighted Matrix

DimensionKeyword / Boolean SearchAiRA Search Matrix
MatchingExact keyword or boolean stringsWeighted, scored attributes
PriorityEvery term counts the sameMust-haves weighted higher
SetupHand-built boolean logicAuto-decoded from the JD
ResultsFlat list, manual triageClosest matches surface first
Source of truthRe-keyed per searchInherited from the approved JD

Key Capabilities

JD → attribute checklist

Eva decodes the approved JD into eight structured attributes: role, skills, education, experience, industry, location, tools and budget.

Relevance weighting

Every attribute is scored, so must-haves pull harder than nice-to-haves instead of flat keyword matching.

Scored filters

Roadmapping 95%, Fintech 92%, SQL / Analytics 88% — each filter carries a relevance weight you can see.

Right people first

The weighted matrix surfaces the closest matches first, not a blunt list of everyone who mentions a keyword.

Precision over boolean

Structured attributes replace long, brittle boolean strings that either miss good people or over-match.

Downstream-ready filters

The matrix feeds sourcing and ranking, so every stage runs on the same definition of a strong fit.

Frequently Asked Questions

What is the AiRA Search Matrix?
The AiRA Search Matrix is a relevance-weighted set of search filters built automatically from your approved job description. Eva Mendis, TheHireHub's Evaluation Matrix agent, reads the JD, decodes it into eight structured attributes — title, skills, experience, industry, location and more — and scores each one so the search targets the people who fit best, instead of anyone who happens to match a keyword.
How is a search matrix different from keyword or boolean search?
Keyword and boolean search treat every term equally and rely on exact string matches, so a critical skill counts no more than an incidental one and near-misses get dropped. The search matrix weights each attribute by relevance — Roadmapping might score 95%, stakeholder management 79% — so candidates are judged on how well they fit the whole role, not on how many keywords they repeat.
Where does the matrix get its attributes?
Straight from the approved JD. Once a job description is signed off, Eva parses it into structured fields and assigns each a weight. Because the matrix inherits directly from the JD, your sourcing criteria always reflect what you actually agreed to hire for — there's no separate search brief to write or keep in sync.
How many attributes does it decode?
Eight. Alongside role and skills, Eva weighs education, career progression, industry, location, tools and budget fit — turning a page of prose into eight live, weighted filters.
Does the search matrix feed the rest of the pipeline?
Yes. The matrix is the criteria layer the downstream steps run on: sourcing uses it to find and score candidates, and ranking reuses the same weights to order the shortlist. Build it once from the JD and every later stage works from the same definition of a strong fit.

Turn your JD into a weighted search

Eva decodes the approved job description into eight scored filters, so sourcing targets the right people first. See the matrix build itself.

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