Search and filter candidates

Three places you can search

Talinty has three search surfaces, each suited to a different question.

Global search lives in the top navigation bar, available from anywhere in the product. Type a name, an email, a skill, or a role title;

results come back from across every role and the talent pool, with the candidate's current status and role next to each result. Use

this when you're looking for a specific person and you don't already know which role they're in.

Candidate List filters live on the dashboard's main Candidate List. Use these when you want to narrow the full pool to the

candidates that match a set of criteria, then work through the resulting list.

Pipeline view filters live inside each role. Use these when you're working a single role and want to slice it (top scorers only,

unattended candidates only, candidates at the Assessment stage only).

Each surface answers a different question. Global search is for a known person; the other two are for known criteria with unknown

people.

Candidate List filters

The Candidate List sits on the dashboard and shows everyone currently in motion across your roles. The filters along the top let you

slice it:

By stage. All, Application, Online Screening, Assessment, Interview, Offer, Hired, Disqualified.

By role. Limit to candidates in one or several specific roles.

By AI score. Set a minimum resume match score, skill match %, or both.

By date. Applied in the last 7 days, last 30, last quarter.

By source. Career page, LinkedIn, job board, referral, manual add, talent pool.

By tag. Custom tags you've applied to candidates (Senior, Bilingual, Open to remote, and so on).

Filters stack. Stage = Assessment AND Resume match ≥ 80 AND Applied in the last 14 days is a valid combination.

[Illustration: Cropped screenshot of the Candidate List filter bar with three or four filters active, and the resulting filtered list below

it. Use anonymous names.]

Saved searches

The filter combinations you use repeatedly can be saved. After applying the filters you want, click Save Search at the top of the list.

Give it a name (High-fit engineers, last 30 days) and decide whether the saved search is private to you or shared with the team.

Saved searches appear in a dropdown above the filter bar. They re-run the filters against current data; the saved search is the

recipe, not a snapshot of past results.

Note for the docs team: confirm whether saved searches exist in the live product and how shared searches behave. The pattern

(named filter combinations, private or shared) is the pattern to keep.

Plain-language search with the AI Assistant

For more complex queries that don't fit cleanly into filters, the AI copilot accepts plain language:

Show me backend engineers who scored above 80 on resume match but haven't been contacted yet.

Find candidates who applied to the Senior PM role and got Disqualified for salary expectations.

Who do we have in the talent pool with Arabic and English fluency?

Talinty AI reads the query, translates it into the equivalent filters and search terms, and shows you the result. It also shows what

filters it applied, so you can see how it interpreted you and adjust if needed.

This is especially useful for the kind of query that takes 30 seconds to build with filter dropdowns but five seconds to describe in

words.

Searching the talent pool

The talent pool is searchable the same way the active candidate list is. Access it from Candidates → Talent Pool in the top

navigation. The same filter set applies (stage doesn't, because pool candidates aren't in a pipeline; everything else does).

Pool searches are how you bring candidates back into active roles. When you find a fit, open the profile and click Add to Role in the

actions panel. The candidate's full history follows them.

Boolean search for power users

For recruiters who came from boolean-heavy tools (LinkedIn Recruiter, Boolean Builder), the global search supports a subset of

boolean syntax:

AND, OR, NOT between terms.

Quotes for exact phrases: "machine learning".

Parentheses for grouping: (python OR ruby) AND backend NOT junior.

The syntax is conservative; not every operator from every tool is supported. The plain-language AI copilot is generally more

powerful for complex queries, but boolean is faster for muscle-memory searches.