NLP-Powered HR Document Automation for Enterprise
An enterprise HR team spent 60% of their time on manual document processing — contracts, onboarding forms, and policy updates.
Team
5 engineers + 1 NLP specialist
Timeline
10 weeks end-to-end
Client
Enterprise Conglomerate (500+ employees)
Outcomes Delivered
78%
Processing Time Reduction
4 hrs → 22 min
Average Document Turnaround
99.1%
Classification Accuracy
How we delivered it
Mapped all 14 document types processed by the HR team, categorising them by volume, complexity, and downstream workflow requirements.
Built a multi-class NLP classifier using spaCy with custom entity recognition for contract terms, employee names, and policy references.
Designed a human-in-the-loop review interface for low-confidence classifications, ensuring accuracy without full automation risk.
Integrated with the client's existing HRIS via API to automatically route extracted data to the correct employee records.
Delivered a 2-week parallel-run period where both manual and automated processing ran simultaneously to validate accuracy before cutover.
What we built
Built an NLP pipeline that extracts, classifies, and routes HR documents automatically, with a human-in-the-loop review interface.
Similar projects
Ready to achieve similar results?
Let's discuss your challenge and design a solution that delivers measurable outcomes — on time and within budget.
Ready to build your next platform? Get a free technical assessment →