Case study • Human Resources — Talent Acquisition / Recruiting Software
NLP-Powered Search Boosts Recruiter Efficiency and Result Accuracy for a Leading TRM Platform
Our client provides a Talent Relationship Management (TRM) platform used by recruiters to search for candidates, companies, and job opportunities. The old search engine was rigid and keyword-based, forcing recruiters to guess the exact terms the system needed. We rebuilt their search engine using natural language understanding, making it easier for recruiters to search the way they think and speak. This increased relevance, reduced search frustration, and improved user satisfaction.
Success Highlights
Key Details
Industry: Human Resources — Talent Acquisition / Recruiting Software Geography: United States
Platform: Web-based TRM platform
Business Challenge
Recruiters needed fast, accurate search to identify candidates, companies, and job opportunities. The platform’s keyword-based engine couldn’t keep up.
The system couldn’t breakdown queries into meaningful parts like , seniority levels, years of experience, company attributes, or job categories. Intent like “recently funded AI companies” or “senior marketers with leadership experience” wasn’t captured for analytics or personalization.
Our Solution Approach
We rebuilt the search engine with natural-language intelligence, transforming how the platform understands, interprets, and ranks recruiter queries.
1 · Discover
Mapping Recruiter Intent & Search Behavior
We analyzed real recruiter search behavior – keyword patterns, failed searches, common filters, and job titles. This helped us identify why searches broke down and what signals (skills, titles, locations, company info) needed to be interpreted for better results.
2 · Interpret
Building the NLP Intelligence Layer
We built an NLP layer that extracted entities such as roles, skills, seniority, industries, and locations from natural-language queries. The system normalized ambiguous input into structured, machine-readable filters. This helped convert vague or incomplete recruiter queries into precise search parameters the engine could rank consistently.
3 · Enhance
Machine-Learning Models for Ranking & Relevance
We implemented ML-based ranking tuned for role fit, skill proximity, seniority alignment, and company attributes. The model improved relevance even when keywords were partial or missing. This helped the platform return high-quality candidates without forcing recruiters to tweak filters or guess system-specific terms.
4 · Experience
Conversational UI Integration
We introduced a conversational search interface that allowed recruiters to enter queries the same way they speak:
Fintech companies hiring Sr. PMs this year
Top AI startups with engineering leadership roles
This reduced the need for filters, saved time, and made the tool much more intuitive.
Technical Highlights
Natural-language entity parsing for People / Company / Job search
Intent classification for recruiter queries
Conversational input converted into structured search parameters
Ranking models tuned for domain-specific relevance
Behavioral analytics to capture user patterns
function processSearchQuery(query):
normalized = normalizeText(query)
entities = extractEntities(normalized)
intent = classifyIntent(normalized)
filters = mapToFilters(intent, entities)
rawResults = searchIndex(filters)
rankedResults = rankResults(rawResults, intent)
return { status: “OK”, data: rankedResults }
Business Outcomes
The platform shifted from rigid, keyword-dependent search to an intent-driven system.Recruiters could finally find People, Companies, and Jobs faster, with fewer refinements and far less friction.
30%
Better Search Relevance
Ranked results aligned with recruiter intent instead of exact keyword matches.
20%
Higher User Satisfaction
Conversational search reduced the need for manual filter adjustments.
⇧
Faster Adoption Across Teams
Modernized UI and smarter ranking shortened candidate discovery time and improved recruiter confidence.
Improved user insight from intent-level behavioral data
Ready to Upgrade Your TRM Search?
Enhance your platform with NLP-driven search, smarter ranking, and a cleaner recruiter experience.
Talk to our team about modernizing your People, Company, and Job search with AI-powered intelligence.