Enterprise recruiter intake

Design the signal scanner around the recruiter, not the other way around.

Capture what counts as a real hiring signal, what should be ignored, where to watch, and how the final output should read. GraniteAi uses that intake to configure collection, ranking, and reporting with enterprise-grade clarity.

Discovery before automation

Talk through a live implementation

Recruiter Intake

Configure the signal scout around real recruiting intent

Capture what matters up front: target roles, signal strength, watch surfaces, and output expectations. The goal is broad enough collection to avoid misses, with enough context to rank what deserves attention.

Autosave

Saved automatically in this browser

Profile and role focus

Define the recruiter context before tuning the scanner.

Recruiter namePreferred emailRecruiting firm or teamRole focus

Collection surface

Choose where the system should look and how aggressively it should browse.

Opportunity types

Seniority

Target companiesPriority peopleGeography

Watch modeDefault watch session (min)Max companies per run

Scoring and noise control

Tell the system what should rank highly and what should be demoted.

Strong indicatorsWeak indicators still worth savingFalse-positive phrasesNegative examples

Ranking preference

Implementation notes

Anything else the system should know about this recruiter's workflow.

Submits directly to our team for configuration.