Goal
The project set out to replace a manual, resume-by-resume hiring process with an AI-driven recruitment engine capable of sourcing, screening, and ranking candidates at scale. The objective was to give a fast-growing talent acquisition team a system that could analyze thousands of LinkedIn profiles a month, surface the right people for the right roles, and push clean, verified data straight into the existing ATS without adding recruiters to keep pace with hiring demand.
Challenge
Before the platform, recruiters were manually searching LinkedIn, copying candidate details into spreadsheets, and re-typing the same information into Zoho Recruit. Skills and experience were judged by keyword scanning rather than context, which meant strong candidates with non-standard resume formatting were routinely missed. Sourcing-to-shortlist for a single requisition took days, hiring managers had no visibility into pipeline health, and the ATS was chronically out of sync with what recruiters actually knew about a candidate.
Outcome
- Time-to-hire cut by 63% by replacing manual screening with AI-driven candidate matching and automated shortlisting.
- 1,240 recruiter hours reclaimed per month through automated LinkedIn sourcing, profile parsing, and ATS data entry.
- 94.2% AI match accuracy, so hiring managers only review candidates who genuinely fit the role’s skills and experience profile.
- 2,847 candidates processed monthly across 43 active requisitions without expanding the recruiting team.
- 98.7% of the sourcing-to-shortlist workflow now runs without manual intervention, from discovery through candidate ranking.
- Real-time Zoho Recruit sync keeps ATS records current within minutes of a match, eliminating duplicate data entry
Services & Tech Stack
Design & Prototyping
Figma
Frontend & Analytics
React Native
Typescript
Recharts
Backend & Integrations
Nest.js
PostgreSQL
Redis
Zoho Recruit API
AI/ML & Matching
Python
spaCy/Ner Models
OpenAI Embeddings
Data Sourcing & Ingestion
LinkedIn sourcing pipeline
Node.js
AWS SQS
Client & Product
RecruitIQ is an AI-powered recruitment operations platform built to automate the heaviest parts of high-volume hiring: candidate sourcing, profile analysis, skills extraction, and job matching. Instead of recruiters manually scanning LinkedIn and re-keying data, the platform runs a continuous AI pipeline that discovers candidates, extracts structured skills and experience data from unstructured profiles, ranks candidates against open requisitions, and syncs verified matches directly into Zoho Recruit — giving recruiting teams a live, self-updating pipeline instead of a static spreadsheet.
Key Challenges Solved
Candidate Discovery at Scale: Automated LinkedIn sourcing continuously identifies candidates matching role criteria, replacing manual boolean-search sourcing with a standing pipeline that runs around the clock.
Unstructured Profile Parsing: NLP models extract skills, titles, tenure, and certifications from inconsistently formatted LinkedIn profiles and resumes, converting free text into structured, comparable candidate data.
Context-Aware Matching: Candidates are scored against job requirements using vector-based similarity rather than keyword overlap, so relevant experience is recognized even when it’s phrased differently than the job description.
Recruiter-to-ATS Handoff: Bi-directional sync with Zoho Recruit removes the manual re-entry step that previously caused pipeline data to drift out of date.
Pipeline Visibility: A live operations dashboard gives recruiting leadership funnel-stage conversion rates and automation performance trends instead of relying on recruiter status updates.
Project stages
1
Analysis & Planning
Recruitment workflow audit
Sourcing criteria and compliance rules definition
Role and use-case documentation (Recruiter, Hiring Manager, Admin)
2
Design & Architecture
Pipeline architecture design
Candidate data model and vector store design
ATS integration planning
3
Development & Testing
LinkedIn sourcing module
NLP parsing and skills extraction
AI matching engine
QA and data-accuracy testing
4
Customization & Support
Staged rollout and hosting
Historical candidate data migration
Recruiter training and onboarding
Documentation and ongoing support
Business Value & Key Features
Automated Inspections
The app adapts to individual needs with tailored workouts and nutrition guidance. By aligning features with user goals, it boosts engagement, satisfaction, and long-term motivation.
AI-Powered Skills Matching
Comprehensive nutrition support with personalized meal plans, dietary guidance, and expert advice from qualified professionals — helping users make smart, informed choices for wellness.
Role-Based Pipeline Management
A dynamic, personalized workout program with targeted and full-body exercises. Users can track progress and build healthier, stronger lifestyles.
Automated ATS Synchronization
Scalable, high-load architecture ensures smooth operation even under heavy data and traffic. Built within budget and requirements, it provides efficiency, security, and long-term value.
Real-Time Recruitment Analytics
Dashboards track candidate volume, hiring funnel conversion by stage, and automation performance trends over time, giving recruiting leadership a clear read on where candidates drop off and where the pipeline is accelerating.
Real Feedback, Real Impact
Diane Foster
Head of Talent Acquisition
Our recruiters used to spend most of their week sourcing and re-typing candidate data instead of actually talking to people. Now the AI handles discovery and screening, and our team focuses on the conversations that matter. We’re filling roles faster with a pipeline that used to feel impossible to keep up with
Got an idea? Let’s build it together
Partner with the team to turn a hiring bottleneck into an AI-driven advantage.
