For Staffing Agencies

Your database is an asset. Start using it like one.

Agencies sit on thousands of CVs that nobody can search, because a CV is a document and not a record. TalentGraph parses the whole archive into structured candidates — skills, tenure, seniority, location — so a new client brief can be matched against people you already know.

What this actually fixes

The three complaints we hear most from teams in this seat.

The archive is dead weight

Ten years of placements, and finding a Python engineer in Pune still means keyword-grepping filenames.

Speed decides the placement

Three agencies got the same brief this morning. The one that submits first, wins.

Redeployment is guesswork

A contract ends Friday and nobody can quickly say who else that person fits.

A week in the new workflow

Four steps, none of which involve reading a CV that was never going to fit.

Bulk-parse the archive

Point the parser at your existing CV store. Each document becomes a structured candidate in the pool.

Structure the client brief

Paste the client's requirement into the Job Parser; it normalizes the title against the O*NET taxonomy.

Match and shortlist

Talent Match ranks the pool against the brief and returns scored candidates with matching and missing skills.

Polish and submit

Resume Builder cleans up formatting and ATS issues before the CV goes to the client — without inventing facts.

Our old parser broke on every two-column resume. This one handles them, and the JSON drops straight into our system.
EX
Name pending
Operations Director — example quote
Placeholder quote.Illustrative, not a real customer — swap in an approved quote or remove this block before launch.

The tools you will live in

Start with these; the rest of the pipeline is there when you need it.

See it on your own staffing agencies workload

Bring a handful of real CVs and one open requisition. Ten minutes is usually enough to tell whether this fits how you work.