AI Candidate Sourcing Agent

Keywords match exact terms – Python matches Python. Semantic search understands meaning – it knows a data engineer with Spark experience is relevant for a machine learning pipeline role even if those words never appear together.

Yes. The agent automatically searches past applicants who made it to final rounds but were not selected. It re-evaluates them against current roles, factoring in any new skills or experience they have gained since.

Yes. The agent searches across internal employees, past applicants in your ATS, silver medalists, and referral networks – presenting the best candidates regardless of source.

ATS keyword search matches exact terms. Gloat's agent uses vector embeddings to find candidates with relevant skills even when their profiles use entirely different terminology. The result is a candidate pool three times larger than keyword search produces from the same database.

Yes. Managers describe the person they need in plain language through Microsoft Teams or Slack. They might type "I need someone who can build data pipelines, has experience with cloud infrastructure, and works well with a small engineering team." The agent interprets that description, runs the search, and returns a ranked shortlist with fit analysis. No Boolean strings, no ATS navigation, no training required.

Gloat's Governance Engine enforces your hiring policies on every search. You define eligibility rules, diversity requirements, internal mobility windows, and approval workflows. The engine logs every candidate surfaced, the ranking logic applied, and the rules checked, creating a full audit trail for compliance and DE&I reporting.

Gloat's Retrieval & Embedding layer uses vector-based semantic search that matches candidates by meaning, not exact terms. A data engineer with Spark experience surfaces for a machine learning pipeline role even when those keywords never appear together in their profile. Traditional ATS systems only return results when exact words match.

Gloat searches across four talent pools in a single query: internal employees, past applicants stored in your ATS, silver medalists from previous hiring rounds, and employee referral networks. The agent ranks all candidates on a single shortlist regardless of source.

Yes, Gloat's Candidate Discovery Agent accepts natural language queries inside Microsoft Teams or Slack. Hiring managers describe the person they need in plain language and receive a ranked candidate slate with fit analysis. No ATS login or Boolean search syntax is required.

Gloat ranks candidates on capability fit, career trajectory alignment, cultural signals, and predicted likelihood to succeed. These rankings draw on models trained across millions of career outcomes in the Knowledge Graph, not keyword frequency or resume recency.