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Client project
Recruitment automation and CRM integration for Profectus
Recruitment automation workflows for Profectus, including resume processing, CRM integration and document-to-deal processing patterns that reduce repetitive administration.
Workflow evidence
Screenshots from the systems and workflows.
These visuals come from the project portfolio and show the workflow, dashboard or training assets behind the case study.
Problem
The operational problem behind the work.
Recruitment and consulting teams receive candidate documents, email attachments and deal information across several systems. Manual extraction and CRM entry slows response times, creates inconsistent data and pulls consultants away from higher-value client and candidate work.
Approach
How the system was shaped.
01
Mapped repeatable intake workflows from email, documents and candidate files through CRM update.
02
Designed extraction workflows to capture candidate and deal information in consistent structures.
03
Added validation and review points before CRM updates.
04
Integrated the workflows with HubSpot and surrounding productivity tools so processed data moved into the operational system.
Architecture
Components that made the work production-minded.
Resume and document intake workflows
AI-assisted information extraction
Validation and exception handling steps
HubSpot API integration
Google and Microsoft productivity integrations
Recruitment retrieval patterns including graph and semantic search where candidate discovery requires it
n8n orchestration for pipeline control and observability
Outcomes
What changed or became possible.
95% reduction in manual data entry
90%+ accuracy pattern for automated deal/email processing
Structured candidate data flow into HubSpot
Reduced repetitive administration for recruitment consultants
Candidate retrieval pattern informed by graph and semantic search work in recruitment contexts
More consistent candidate records for downstream search and matching
Responsible AI
Why governance is part of the implementation.
Human review remains important where extracted data affects candidate records.
The workflow focuses on administrative processing and recruiter support, not automated hiring decisions.
Structured validation reduces the risk of silent data quality issues entering the CRM.
Candidate retrieval patterns should remain explainable and reviewable when used in recruitment contexts.
Stack
Tools and platforms used.
n8nHubSpotLlamaIndexDocument ProcessingGoogle APIsMicrosoft 365Workflow Automation
Similar challenge?
Start by assessing the workflow, data and risk.
The AI Readiness Audit is the cleanest first step when you need to decide what to automate, what to avoid, and what should be governed before a production build.