Recruiter Copilot
Identify and match the right technical experts to critical projects using AI-driven capability mapping and skill insights. Our document-grounded, reasoning-capable assistant helps digital infrastructure teams identify high-potential candidates across internal resume data.
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Executive summary
Traditional resume search cannot keep pace with the complexity of modern technical hiring. This reasoning-driven solution interprets natural-language prompts, retrieves structured resume data, and ranks candidates by inferred intent and fit with verifiable transparency. Built on SeekrFlow’s agentic architecture and AI-Ready Data Engine, it delivers explainable, auditable results that integrate across enterprise workflows. The outcome is faster, more reliable team formation and a repeatable, compliant framework for discovering technical talent with confidence.
Problem
Fast-moving engineering and AI organizations need to form capable teams quickly, but traditional search tools miss nuance. Keyword filters overlook hybrid skillsets, leadership signals, and adjacent experience that often define great hires.
Hiring managers don’t ask for “React + SQL”—they ask things like:
“Who’s worked in fintech, led backend systems, and could grow into a team lead role?”
“Who’s contributed to open source and understands geospatial data?”
“Who could ramp up on AI product work, even without direct model training experience?”
These are multi-step, inference-heavy questions, and most tools can’t answer them.
Solution
This prebuilt solution transforms complex hiring queries into multi-step reasoning flows. Stakeholders use natural language to surface candidates who match inferred intent, not just surface-level tags.
Each result includes:
Hyperlinked resumes for fast handoff
Grounded responses with clear citations
Multi-turn query support (follow-ups, refinements, chaining)
Value
Answers complex talent questions, not just keyword matches
Surfaces high-potential candidates who’d be missed by filters
Accelerates formation of high-impact teams
Explainable, auditable results—not black-box guesses
Extensible: adapt it with your own success traits, history, or enrichment layers
How it works
This solution uses SeekrFlow’s modular agent architecture:
Planner
Interprets hiring prompts, infers structure and intent
Executor
Retrieves structured resume chunks using FileSearch
Evaluator
Scores results based on relevance, depth, and clarity
Thread-aware
Supports multi-turn queries and session cleanup via UI or SDK
SeekrFlow’s AI-Ready Data Engine handles resume ingestion, chunking, and metadata tagging—no extra training or ops required.
Ideal users
Engineering and product leads forming agile teams
AI team managers staffing cross-functional initiatives
Talent ops and internal mobility specialists
ICT orgs managing large-scale internal staffing pools
Built on SeekrFlow
AI-Ready Data Engine
Resume chunking, metadata tagging
FileSearch
Hybrid search over internal resume corpora
Agent Framework
Planner, Executor, Evaluator
Evaluation Engine
Optional scoring for every result
Web UI & SDK
End-to-end access without notebooks or ops
Where you can extend it
This Prebuilt Solution is fully extensible via SeekrFlow UI, SDK, or pipeline updates:
Fine-tune with past hire data or internal success traits
Add new resume sources, project histories, or GitHub enrichment
Chain to outreach tools or summary generators
Integrate recruiter feedback to refine matching over time
Takeaway
This isn’t resume search—it’s a reasoning-powered copilot for talent strategy. Deployed on SeekrFlow, it helps technical orgs discover, evaluate, and assemble the right team faster and more intelligently than traditional filters ever could.
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See it in action
See how this AI solution works for your team. Request a live walkthrough with one of our experts and explore how it can adapt to your unique workflows and data.
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