About the Client

Client	HR Mind — a Profiler Group Company
Industry	Global Recruitment & Workforce Management
Sectors	Industrial · E-commerce · Infrastructure & EPC · Renewable Energy · Automotive · IT · Healthcare · FMCG
Experience	9 years  |  global leader in recruitment and workforce management strategies
Website	hrmind.com
Delivered by	Peritos Solutions

HR Mind is a global recruitment and resourcing company with 9 years of industry experience, serving clients across Industrial, E-commerce, Infrastructure & EPC, Renewable Energy, Automotive, IT, Healthcare, FMCG, and Consumer Durables sectors. As a Profiler Group company, HR Mind brings enterprise-grade workforce management strategies to clients worldwide.

Project Background

HR Mind required a new website that reflected their standing as a global recruitment leader — professional, fast, and capable of generating qualified leads from both candidates and employers across their 8+ industry verticals. Their previous web presence did not represent their brand effectively, lacked CRM integration, and was not optimised for search engine visibility. 

Peritos Solutions was engaged to deliver the complete project end-to-end: brand-aligned UI/UX design, WordPress development, CRM lead generation integration, and production hosting on AWS — all within a compressed one-month timeline. The requirement was a site that would rank on Google, load fast globally, capture leads automatically, and stay online reliably.

Project Timelines

Phase	Week	Key Activities	Status
Phase 1	Week 1	Discovery & planning — requirements, sitemap, wireframes, AWS architecture design, domain & DNS setup (Route 53)	Done
Phase 2	Week 1–2	UI/UX design — brand-aligned page designs, mobile-responsive layouts, CRM lead form wireframes reviewed & signed off	Done
Phase 3	Week 2–3	Development — WordPress/CMS build, all pages coded, CRM integration (HubSpot/Zoho), contact & lead capture forms live	Done
Phase 4	Week 3	AWS infrastructure setup — EC2, S3, RDS, CloudFront CDN, ACM SSL, IAM roles, AWS Backup, CloudWatch monitoring configured	Done
Phase 5	Week 3–4	SEO implementation — on-page SEO, meta tags, schema markup, XML sitemap, robots.txt, Google Search Console & Analytics setup	Done
Phase 6	Week 4	QA, performance testing, Core Web Vitals validation, UAT sign-off, DNS cutover, go-live & 2-week hypercare support	Done

Scope & Requirements

Website Design & Development

• Brand-aligned UI/UX design — mobile-first, responsive layouts across all pages 

• WordPress CMS build — enabling HR Mind’s team to manage content independently post-launch 

• Pages: Home, About, Industries (8 verticals), Services, Careers, Contact 

• Lead capture forms — candidate registration, employer enquiry, and job submission forms 

• Performance optimisation — image compression, lazy loading, minified CSS/JS, Core Web Vitals compliance 

CRM Lead Generation Integration

• CRM integration (HubSpot / Zoho) — all form submissions routed directly to CRM pipeline 

• Lead segmentation — candidate vs. employer leads tagged and routed to separate CRM pipelines 

• Automated email notifications — internal team alerted on new lead submission 

• UTM parameter tracking — all CRM leads tagged with source, medium, and campaign for ROI reporting 

SEO Optimisation

• On-page SEO — title tags, meta descriptions, H1/H2 structure, keyword-optimised copy for all pages 

• Technical SEO — XML sitemap, robots.txt, canonical tags, structured data (schema markup) 

• Google Search Console and GA4 setup — tracking, indexing, and performance monitoring from day one 

• Core Web Vitals — LCP, FID, and CLS all passing green on both mobile and desktop at launch 

AWS Hosting & Infrastructure

• Amazon EC2 (t3.medium) with Auto Scaling Group — scales up automatically under traffic spikes 

• Application Load Balancer — distributes traffic across EC2 instances with health checks 

• Amazon RDS MySQL Multi-AZ — production database with automatic failover and daily snapshots 

• Amazon S3 — static asset storage, media library, and backup storage 

• Amazon CloudFront CDN — global content delivery from 400+ edge locations 

• Amazon Route 53 — DNS management with latency-based routing 

• AWS ACM — free SSL/TLS certificate provisioned and auto-renewed 

• AWS WAF — web application firewall protecting against OWASP Top 10 threats 

• AWS Backup — automated daily backups, 30-day retention, cross-region recovery 

• Amazon CloudWatch + SNS — uptime monitoring, CPU/memory alarms, email alerts 

Implementation

Week 1 — Discovery & Architecture

Peritos ran a rapid discovery sprint covering HR Mind’s brand guidelines, target audience (candidates and employers across 8 sectors), CRM system, and hosting requirements. The AWS architecture was designed and presented for sign-off — service selection justified against traffic profile, budget, and availability targets. Domain and DNS were migrated to Route 53 immediately to begin SSL provisioning via ACM. 

Week 2 — Design & Development

UI/UX designs were produced in Figma, reviewed, and signed off by HR Mind within 3 business days. WordPress development commenced in parallel — custom theme built from approved designs, all pages developed, and CRM lead capture forms integrated and tested end-to-end. Mobile responsiveness and cross-browser compatibility validated across Chrome, Safari, Firefox, and Edge. 

Week 3 — AWS Infrastructure

The full AWS production stack was provisioned: EC2 instance launched and configured, RDS MySQL Multi-AZ database deployed, S3 bucket configured for media and backups, CloudFront distribution created with custom domain and ACM SSL, WAF rules applied, IAM roles locked down to least-privilege, and AWS Backup policies set. CloudWatch dashboards and SNS alarms configured for uptime, error rate, and resource utilisation. 

Week 4 — SEO, QA & Go-Live

On-page SEO implemented across all pages — meta tags, schema markup, XML sitemap submitted to Google Search Console, GA4 tracking verified. Full QA pass covering functional testing, form submission flows, CRM lead routing, load testing, and Core Web Vitals audit. DNS cutover executed during a low-traffic window, SSL confirmed live, and the site went live within the agreed timeline. 

Application screenshots placeholder — insert homepage, industry pages, lead capture form, CRM pipeline, and AWS console views here.

Results & Impact

Observability & Visibility

Assessment Report

Before development commenced, Peritos conducted a rapid discovery and assessment covering: 

• Risk & Gap Analysis — reviewed HR Mind’s existing web presence, identified SEO gaps, CRM integration requirements, and hosting constraints before any design or build work began 

• Customised Assessment Report — delivered a scoped architecture proposal covering AWS service selection, CRM integration approach, SEO strategy, and go-live timeline within the first week 

• AWS architecture confirmed — service selection (EC2, RDS Multi-AZ, CloudFront, Route 53, WAF, Backup) validated against HR Mind’s traffic profile and availability requirements before infrastructure provisioning 

Cloud Formation

AWS Infrastructure

The complete AWS stack was provisioned, configured, and hardened within week 3 of the engagement: 

• Multi-AZ RDS deployment ensures database availability with automatic failover — zero downtime for planned maintenance 

• CloudFront CDN delivers static assets from 400+ global edge locations — reducing load times by 3x for international candidates and employers 

• AWS Backup configured with daily automated snapshots, 30-day retention, and cross-region backup for full disaster recovery coverage 
• AWS WAF protects against common web exploits, SQL injection, and DDoS — all traffic inspected before reaching the application layer 

Technology & Architecture

Compute	Amazon EC2 (t3.medium)  |  Auto Scaling Group  |  Application Load Balancer (ALB)
Storage	Amazon S3  |  static assets, media, backups  |  S3 Versioning enabled
Database	Amazon RDS (MySQL)  |  Multi-AZ deployment  |  automated snapshots
CDN & DNS	Amazon CloudFront  |  global edge caching  |  Amazon Route 53  |  SSL via AWS ACM
Security	AWS IAM  |  least-privilege roles  |  AWS WAF  |  Security Groups  |  ACM SSL/TLS
Backup	AWS Backup  |  automated daily snapshots  |  30-day retention  |  cross-region backup
Monitoring	Amazon CloudWatch  |  uptime alarms  |  CPU & memory metrics  |  SNS email alerts
CMS / Frontend	WordPress  |  custom theme  |  mobile-responsive  |  Core Web Vitals optimised
CRM Integration	HubSpot / Zoho CRM  |  lead capture forms  |  contact routing  |  pipeline automation
SEO	Yoast SEO  |  XML sitemap  |  schema markup  |  Google Search Console  |  GA4

Architecture Overview

Challenges

Compressed One-Month Timeline

Design, development, CRM integration, AWS setup, SEO, and go-live all within four weeks required strict parallel workstreaming. Peritos ran design and development concurrently, began AWS provisioning in week 2 (before development was complete), and ran SEO implementation in parallel with QA — compressing what is typically a 2–3 month engagement into four weeks without cutting scope. 

Multi-Sector Content Architecture

HR Mind operates across 8 industry verticals — each requiring distinct messaging, keywords, and page structure for SEO effectiveness while maintaining a consistent brand. Peritos designed a templated industry page structure that HR Mind’s team can replicate for new verticals independently, without developer involvement. 

CRM Lead Routing Logic

Candidate and employer leads required different routing rules, pipeline stages, and internal notification recipients within the CRM. Peritos mapped the full lead lifecycle before development, built conditional routing logic into the form integration layer, and tested all paths end-to-end before go-live. 

DNS Cutover with Zero Downtime

Migrating DNS from the previous hosting provider to Route 53 required careful TTL management and timing to avoid any window of downtime. Peritos lowered TTLs 48 hours before cutover, executed the switch during a low-traffic period, and had the old origin on standby for immediate rollback — the cutover completed with no downtime recorded. 

Key Benefits

• Live in under 1 month — full design, build, AWS hosting, CRM integration, and SEO delivered end-to-end in under 4 weeks 

• Automated lead generation — every candidate and employer enquiry flows directly into the CRM pipeline with zero manual handling 

• Global performance — CloudFront CDN ensures fast load times for HR Mind’s international audience across all 8 industry sectors 

• Enterprise-grade security — AWS WAF, IAM least-privilege, ACM SSL, and Security Groups protect the site and its data at every layer 

• Fully recoverable — AWS Backup with 30-day retention and cross-region recovery ensures HR Mind’s site and data can be restored from any failure scenario 

• SEO-ready from day one — Core Web Vitals passing, Google Search Console live, and structured data in place before the first visitor arrived 

• Self-manageable CMS — WordPress enables HR Mind’s team to update content, add jobs, and manage pages independently without developer support 

Post-Launch Support

Hypercare Period

A 2-week hypercare period was included post go-live. During this period Peritos monitored CloudWatch metrics daily, resolved any content or performance issues identified by HR Mind’s team, and made minor CRM routing adjustments based on real lead data. All CloudWatch alarms, backup policies, and WAF rules were reviewed and tuned before formal handover. 

 Full handover documentation covering AWS architecture, WordPress admin guide, CRM lead routing logic, and DNS management was delivered to HR Mind at the close of the hypercare period.

Module 1 — Appointment Booking & Management

A centralized, real-time appointment management system for walk-in and online bookings:  Schedule, reschedule, and cancel appointments with a single click — centralized dashboard with real-time queue and wait times  Support for walk-in and online appointment channels — quick-access buttons for both  Patient registration at booking — captures name, gender, DOB, mobile, Aadhaar/ABHA ID  New ABHA account creation directly from the appointment interface — or verification of existing ABHA ID  Real-time appointment tracking — arrival status, wait time, consultation status all visible in one view  View patient vitals, medical history, prescriptions, and previous examination notes directly from the appointment dashboard  Action controls: view detail, update time, reschedule, cancel — with confirmation prompts  Department and doctor selection — appointments routed to the correct consultant automatically  Integration with ABHA for secure digital health record access and sharing at the point of booking

 

Module 2 — Patient Management

Complete end-to-end patient record management — from first registration to ongoing care:  Unique UHID (Universal Health ID) generated for every patient at registration  Comprehensive patient profile: demographics, medical history, allergy triggers, vital alerts, immunisation records  Visit logs and doctor assignment history across all OPD and IPD interactions  Consent logs and documented approvals — legally compliant patient consent management  Integrated view across prescriptions, appointments, billing, and lab reports — all accessible from a single patient record  Vital signs dashboard: height, weight, BMI, temperature, pulse, blood pressure — all logged per visit  ABHA / Aadhaar linking — patient records linked to national health identity for interoperability

 

Module 3 — Laboratory Management (Diagnostic Centre)

End-to-end lab workflow management — from test assignment to report delivery — purpose-built for diagnostic centres:  Test assignment from doctor to lab — linked directly to patient profile by name, ID, or ABHA number  Sample ID generation and tracking — collection date, dispatch, acknowledgement, processing status all tracked  Priority-based sample handling — urgent samples flagged and processed with higher priority  Result entry: both automated (machine connectivity) and manual input options  Automated report verification alerts — notifies lab doctors and physicians when results are ready for review  PDF lab report generation with one click — auto-distributed to patient, treating doctor, and relevant staff  Outsourced sample management — supports samples sent to external reference labs  Integrated patient history — view all past tests and results from the same interface  ABHA-compatible — search and link patients using national health ID for paperless lab processing  Role-based access — lab assistants, technicians, and consultants each see only relevant data and actions  Diagnostic machine connectivity — direct integration for automated result capture, reducing manual errors

 

Module 4 — AI Prescription Generation & Clinical Intelligence

The AI layer is the most powerful differentiator in Ektos Health — enabling doctors to generate accurate, formatted prescriptions in under a minute using voice or text, with AI-assisted diagnosis support:  Voice-to-Text Prescription Dictation  Doctors dictate the prescription verbally — the system converts speech to structured prescription text in real time  Supports medical terminology, drug names, dosages, and clinical instructions accurately  Significantly reduces consultation time — doctors spend less time typing and more time with the patient  Dictated text is editable before finalisation — doctor retains full clinical control  AI-Generated Diagnosis Suggestions  Doctor enters the patient’s chief complaint and clinical notes — AI analyses these against the patient’s previous diagnosis history  AI suggests probable diagnoses ranked by likelihood — based on the symptom pattern, history, and clinical context  Differential diagnosis support — highlights conditions to rule out based on the presenting complaint  AI draws from the patient’s full longitudinal history stored in the system — not just the current visit  Doctor reviews, selects, or overrides AI suggestions — the system learns and improves with usage  AI Prescription PDF Generation  Once the consultation is complete, the system generates a professionally formatted, branded prescription PDF automatically  Prescription includes: patient details, date, doctor name and registration number, diagnosis, medications with dosage and frequency, instructions, follow-up date  Compliant with ABDM digital prescription standards — can be shared electronically via ABHA  Prescriptions stored against the patient record — visible in appointment history and patient profile  Configurable prescription templates per department or doctor — managed via Settings module

 

Module 5 — Admission & Discharge (IPD)

Full inpatient lifecycle management — from bed allocation on admission to discharge summary generation:  Digital patient registration at admission — captures insurance details, ID, health history, and emergency contacts  Intelligent bed allocation — auto-assigns beds based on availability, room type (ICU, General, Private, Isolation), and clinical condition  Real-time bed management dashboard — live view of all bed IDs, types, room numbers, and occupancy status  Bed category management — ICU, General, Private, Isolation configured and managed via the system  Real-time patient condition monitoring — clinicians and nursing staff track status updates and discharge readiness  Discharge planning — clinicians set discharge timelines and manage pending reports before release  Automated discharge summary generation — produced with a few clicks, including diagnosis, treatment summary, medications, and follow-up instructions  Bed released automatically on discharge — status updated from ‘In Use’ to ‘Available’ in real time  Cross-department coordination — admission, billing, nursing, and housekeeping all notified of status changes  Care team collaboration dashboard — doctors, nurses, and admin work from the same centralized view

 

Module 6 — Billing Management

Integrated, transparent billing across all hospital services — from OPD consultations to lab tests and inpatient stays:  Automated bill generation — charges for consultations, lab tests, procedures, medications, and room rental all captured automatically  Multi-status billing — tracks paid, unpaid, partially paid, and refunded invoices  Detailed payment breakdown per patient — line-item visibility of every charge  Patient-wise billing history — all bills and payment records linked to the patient profile  Search and filter tools — quickly locate invoices by patient, date, doctor, or billing status  Consent-based billing — billing actions linked to documented patient consent  Invoice and billing templates configurable per hospital — managed via Settings module

 

Module 7 — Settings, Master Data & System Configuration

Full control over how Ektos Health operates within your institution:  Brand settings — hospital logo, colours, and name applied across all reports, prescriptions, and invoices  Email and SMS configuration — automated notifications for appointment confirmations, lab results, and billing  Invoice, prescription, appointment, and lab report templates — all configurable without developer involvement  User roles and access control — granular permissions per role (doctor, nurse, lab technician, billing staff, admin)  Compliance and audit trails — all actions logged with user ID, timestamp, and action type  Department management — add, edit, and deactivate departments and specialties  Doctor and staff profiles — registration numbers, specialties, and schedule management  Billing item setup — configure service codes, pricing, and insurance billing items  Real-time system updates — configuration changes take effect immediately without downtime

ABDM Compliance	Full integration with Ayushman Bharat Digital Mission — ABHA creation, verification, and health record linkage built into appointment, lab, and prescription workflows
ABHA Integration	Patients can create a new ABHA (Ayushman Bharat Health Account) or link an existing one at registration — enabling secure nationwide health record interoperability
Aadhaar Verification	Aadhaar-based patient identity verification supported at registration and appointment booking
Digital Prescriptions	AI-generated prescription PDFs comply with ABDM digital prescription standards — shareable via ABHA
NABH Standards	Workflow design, documentation requirements, consent management, and audit trails align with NABH accreditation criteria
Audit Trails	All clinical and administrative actions logged with user, timestamp, and action type — supporting NABH audit requirements
Data Security	Patient health data encrypted at rest and in transit — role-based access prevents unauthorised data exposure
Compliance Readiness	90% compliance readiness score across ABDM/NABH requirements — hospitals go live already meeting accreditation benchmarks

Technology & Architecture

Ektos Health is a cloud-native application built on modern web technologies, deployed on scalable cloud infrastructure:

Frontend	React.js — fast, responsive, mobile-compatible web interface — works on desktop, tablet, and mobile without a separate app
Backend	Node.js / Python REST APIs — microservice architecture for each module (appointments, lab, billing, AI)
Cloud	Cloud-hosted — scalable, high-availability infrastructure with 24/7 uptime monitoring
Database	Secure relational database with full patient record history, audit logs, and real-time updates
AI Engine	GPT-4 integration for diagnosis suggestions and prescription generation — custom prompt engineering for clinical context
Voice-to-Text	Speech recognition API with medical vocabulary training — dictation converted to structured prescription text
PDF Engine	Automated prescription and lab report PDF generation — templated, branded, and configurable per department
ABDM API	Official ABDM API integration — ABHA creation, verification, and health record exchange
Notifications	SMS and email notification engine — appointment reminders, lab result alerts, billing confirmations
Security	Role-based access control, encrypted data transmission, session management, and full audit logging

AI Features — How They Work

AI Feature	How It Works	Clinical Benefit
Voice-to-Text Prescription	Doctor speaks the prescription aloud. Speech recognition converts dictation to structured text — drug names, dosages, instructions — in real time. Doctor reviews and confirms before saving.	Consultation time reduced significantly. Doctor maintains eye contact with patient rather than typing. Reduces transcription errors.
AI Diagnosis Suggestion	Doctor enters chief complaint and clinical notes. AI analyses these against the patient’s stored diagnosis history and symptom patterns to suggest probable diagnoses ranked by likelihood.	Supports junior doctors with differential diagnosis. Reduces diagnostic oversight. Highlights conditions to rule out. Improves clinical decision quality.
AI Prescription PDF	Once diagnosis and treatment are confirmed, the system auto-generates a formatted, branded prescription PDF including patient details, diagnosis, medications with dosage and frequency, and follow-up date.	Professional, legible, legally compliant prescriptions every time. Stored against patient record. Shareable via ABHA. No formatting overhead for doctor.
Previous Diagnosis Context	AI accesses the patient’s full longitudinal history — all previous diagnoses, medications, allergies, and test results — as context when generating suggestions for the current visit.	Prevents prescribing contraindicated medications. Highlights recurring conditions. Improves continuity of care across multiple visits and doctors.

Implementation Approach

Ektos Health is deployed as a cloud SaaS product. New hospitals and diagnostic centres can be onboarded and live within days:

Day 1–2 — Setup	Hospital profile, branding, departments, doctors, and billing items configured in Master Data and Settings. User roles and access levels assigned.
Day 2–3 — Integration	ABDM/ABHA API connection configured. SMS/email notification templates set up. Diagnostic machine connectivity tested where applicable.
Day 3–4 — Data Entry	Existing patient records migrated or entered. Lab test catalogue configured. Room and bed categories set up for IPD centres.
Day 4–5 — Training	Staff training on appointment, lab, billing, and prescription workflows. Doctors trained on voice-to-text and AI diagnosis features.
Day 5 — Go-Live	Live patient appointments and consultations begin. Peritos Solutions provides hypercare support for the first two weeks post-launch.
Ongoing	24/7 cloud support. Feature updates deployed automatically. AI model improves with usage. ABDM regulatory updates applied centrally.

Client Testimonials

“Ektos Health has significantly streamlined our operations and improved efficiency across our healthcare workflows. The platform is intuitive, reliable, and backed by a highly responsive team at Peritos Solutions.”  — Akanksha Niranjan, Director, Ekanshi Solutions, Lucknow

“The platform has simplified our day-to-day clinic management, from patient records to reporting. It has reduced manual work and improved overall efficiency. The support team is proactive and always available when needed.”  — Dr. Ramnath Mishra, Clinic, Bhubaneswar

“Ektos Health has transformed how we manage patient records and hospital operations. The system is easy to use, secure, and provides quick access to critical information, enabling us to deliver better patient care.”  — Dr. Anil Chowdhary, Lal Kothi Hospital, Jaipur

About HR Mind

HR Mind is a global resourcing company founded in 2010 that offers end-to-end recruitment and HR solutions to organisations in domestic and international markets. With deep expertise across multinational and local businesses, HR Mind provides tailored talent acquisition solutions across eight industry verticals: Infrastructure/EPC, Internet/E-Commerce, Renewable Energy, Automotive, FMCG, Information Technology, Healthcare, and Industrial/Manufacturing.

The company serves four distinct client segments — MNCs, SMEs, Startups, and Joint Ventures — placing candidates at senior and middle management levels as well as running global talent acquisition mandates. Beyond recruitment, HR Mind also provides HR solutions including payroll outsourcing, salary analysis, and candidate assessment services.

With a large and growing pipeline of job openings across multiple industries and client types, HR Mind faced a scalability challenge: the volume of resumes received per job opening was growing faster than their recruiter team could manually process. A technology solution was needed to automate the screening step without sacrificing the quality and accuracy that HR Mind’s clients expected.

The Problem

Recruitment at scale is fundamentally a data matching problem — but one that had been solved manually for decades. HR Mind identified several specific pain points driving the need for an AI solution:

• High volume, low signal — hundreds of resumes received per job opening, with the majority not matching the role requirements. Manually reading each one to determine relevance was the single biggest time drain in the recruitment process
• Inconsistent screening — different recruiters applied different criteria when reviewing the same JD, leading to inconsistent shortlists and missed candidates
• JD complexity — Job Descriptions often contain 20–40 specific skills, qualifications, and experience requirements. Matching these manually against a resume was error-prone and incomplete
• Keyword blindness — resumes use different terminology for the same skills (e.g. ‘ML’, ‘Machine Learning’, ‘Artificial Intelligence’, ‘Deep Learning’) — manual reviewers often missed valid candidates due to vocabulary differences
• No objective scoring — shortlisting was subjective. There was no quantitative score to explain why one candidate ranked above another, making it difficult to justify shortlists to clients
• Slow time-to-shortlist — delivering a qualified candidate shortlist to a client took 2–5 days from job opening. In competitive talent markets, this delay cost placements
• Inability to re-use candidate pool — past resumes in the database were not being systematically re-matched against new job openings — a significant lost opportunity

Scope & Feature List

Solution Architecture

The platform is built entirely on AWS serverless architecture — no servers to manage, automatic scaling with application volume, and pay-per-use pricing that keeps costs proportional to usage:

Layer	AWS Service / Technology	Role in HR Mind Platform
Ingestion	AWS S3	Secure storage for all uploaded resumes (PDF, Word, text) — triggers Lambda functions on upload for automatic processing
Document Parse	AWS Textract	Extracts structured text from PDF resumes including scanned documents — feeds clean text to the NLP pipeline
NLP / AI	AWS SageMaker + Lambda	ML models for resume classification, keyword extraction, semantic matching, and candidate scoring — deployed as serverless endpoints
Text Embeddings	Amazon Bedrock	NLP entity extraction and semantic understanding — identifies skills, job titles, organisations, and dates from unstructured resume text
Matching Engine	AWS Lambda	Serverless function orchestrating JD parsing, keyword extraction, resume-to-JD matching, and score calculation — triggered per job opening
API Layer	Lambda Direct URl	RESTful API endpoints for recruiter dashboard, resume upload, JD submission, shortlist retrieval, and candidate search
Data Store	SQL DB	NoSQL database storing structured candidate profiles, match scores, JD keyword profiles, shortlists, and recruiter actions
Auth	Auth0	Recruiter and admin authentication — role-based access to platform features and candidate data
Monitoring	AWS CloudWatch	Performance monitoring, error alerting, Lambda invocation metrics, and cost tracking dashboards
Security	AWS WAF + IAM	Web Application Firewall protecting API endpoints; IAM roles enforcing least-privilege access to all AWS resources
Storage Archive	S3 Lifecycle Policies	Automatic archival of old resumes to S3 Glacier — cost management for long-term candidate data retention

End-to-End Workflow

Step 1 — JD Upload	Recruiter uploads or pastes the Job Description into the platform. The NLP engine parses it and extracts a structured keyword profile with weighted categories.
Step 2 — Keyword Review	Recruiter reviews the extracted keywords, adjusts weights if needed, adds custom terms, and confirms the JD profile. The AI is now primed for matching.
Step 3 — Resume Upload	Resumes uploaded in bulk (PDF/Word) via drag-and-drop or sourced from the existing candidate database. AWS S3 stores each file and triggers automatic processing.
Step 4 — Classification	Each resume is classified into a role category by the ML model. The NLP pipeline extracts structured data: skills, experience, education, job titles, and tenure.
Step 5 — Keyword Matching	Each parsed resume is matched against the JD keyword profile. Exact and semantic matches are scored. Skills gaps are identified. An overall match score (0–100) is calculated.
Step 6 — Review & Export	Recruiter reviews the ranked shortlist, filters by threshold if needed, compares top candidates side-by-side, and exports the final shortlist for client presentation.
Step 7 — Database Update	All candidate profiles and scores are stored in DynamoDB. As new JDs are posted, stored candidates are automatically re-evaluated — making the talent pool smarter over time.

Challenges & Solutions

Resume format diversity	Resumes arrive in PDF, Word, scanned images, and plain text. AWS Textract handles all formats including scanned PDFs — ensuring no resume is unreadable by the system.
Vocabulary mismatch	Candidates and JDs use different terms for the same skill. Semantic NLP embeddings via Amazon Comprehend identify conceptually similar terms, preventing valid candidates from being missed.
Explaining AI ranking to clients	Clients needed to understand why a candidate ranked where they did. The platform generates a transparent score breakdown per candidate — every ranking decision is explainable.
Scaling for peak volume	Recruitment campaigns can generate hundreds of applications overnight. AWS Lambda’s serverless model scales to process any number of resumes in parallel with no infrastructure provisioning required.
Bias in recruitment	Automated ranking risks encoding historical bias. The scoring model is built on skills and experience alignment only — personal identifiers are excluded from all scoring calculations.
Stale candidate database	Stored resumes quickly became outdated if not re-evaluated. The platform automatically re-scores all existing candidates against each new JD — keeping the talent pool continuously active.
Multi-industry keyword sets	HR Mind operates across 8 industry verticals — each with distinct terminology. The keyword taxonomy is industry-aware, with sector-specific skill libraries built for each vertical.

Key Benefits

• Resume screening time reduced by up to 90% — what took recruiters days now takes the AI minutes
• Objective, explainable candidate ranking — every shortlist position is backed by a transparent score breakdown, not recruiter intuition
• Semantic keyword matching eliminates vocabulary-based false negatives — valid candidates are no longer missed because they used different terminology
• Bulk processing on AWS Lambda — 100+ resumes processed in parallel with no performance degradation or infrastructure cost
• Continuous talent pool intelligence — stored candidate profiles are automatically re-evaluated against every new JD, turning the database into a living, searchable asset
• Faster time-to-shortlist — from days to minutes — enabling HR Mind to deliver shortlists to clients faster and win more competitive mandates
• Multi-industry ready — keyword taxonomies cover all 8 of HR Mind’s industry verticals, with recruiter-adjustable profiles per role type
• Bias-mitigated ranking — scoring based solely on skills, experience, and JD fit — personal identifiers excluded from all ranking calculations
• Strapi CMS deployed in a VM.
• Client-ready shortlist exports — formatted PDF or CSV shortlists with match scores and summaries, ready for client presentation in one click

Implementation Approach

Peritos Solutions delivered the platform in phases, with HR Mind recruiters involved at every stage to validate AI output quality against their own domain expertise:

Phase 1 — Discovery	Recruitment workflow analysis, JD structure review across 8 industry verticals, resume format audit, keyword taxonomy design, AWS architecture design
Phase 2 — Data Pipeline	AWS S3 ingestion setup, Textract PDF parsing pipeline, resume text extraction and cleaning, DynamoDB schema design for candidate and JD profiles
Phase 3 — NLP & ML Models	Resume classification model training, keyword extraction pipeline (Amazon Comprehend + custom), semantic embedding layer for vocabulary mismatch handling
Phase 4 — Matching Engine	JD keyword extraction, weighted scoring algorithm, semantic matching layer, composite ranking engine, skills gap analysis module
Phase 5 — Dashboard	Recruiter interface build — React.js frontend, API Gateway integration, bulk upload UI, ranked shortlist view, candidate comparison, export functionality
Phase 6 — Testing & Tuning	Recruiter validation of AI shortlists vs manual shortlists — model tuning to align AI output with HR Mind domain expertise; bias audit
Phase 7 — Go-Live	Production deployment on AWS, CloudWatch monitoring setup, recruiter training, hypercare support period, ongoing model improvement pipeline

Support & Next Steps

Peritos Solutions manages the AWS environment as an ongoing cloud partner — monitoring costs, model performance, and system stability. The AI models improve continuously as more resumes and JDs are processed through the platform.

Planned next phase enhancements:

• Video interview analysis — AI assessment of candidate video interviews, scoring communication skills and cultural fit signals
• Candidate outreach automation — automated, personalised outreach to top-ranked candidates via email and LinkedIn based on match scores
• Salary benchmarking integration — match scores combined with HR Mind’s salary analysis data to provide candidates with market compensation intelligence
• Real-time job board integration — automatic ingestion of applications from job boards (LinkedIn, Indeed, Naukri) directly into the AI pipeline
• Client portal — direct client access to AI-ranked shortlists with the ability to provide feedback that further trains the model to client-specific preferences
• Multi-language resume support — NLP pipeline extended to process resumes in French, Chinese, and other languages for HR Mind’s global operations

About Client

Pioneer Group has been in the education field past 1996. Pioneer Public School might be a new name in the education industry but people are well-versed with Pioneer Institute of Professional Studies and Pioneer Convent. The school focuses on providing a blend of education and culture to its students.

• Offers children basic and advance facilities while imparting easy education
• Teaches children through audio-visual modules
• A staff of trained teaches that focuses on giving an all-round development to the students

http://www.pioneerpublicschool.com/

Location: Indore, Madhya Pradesh, India

Project Background- Online Attendance Management

Pioneer Public School got together with Peritos to discuss the struggles of maintaining attendance records in online classes during lockdown. Peritos instantly suggested the school attendance tracking app as it is easy to use and all the information is just a click away. Also, the school attendance tracking software will give the liberty of making the entire process of attendance, class schedule and timings transparent for students, teachers and even parents. This was implemented first for Pioneer Institute Of Professional Studies which is an organization in the same group after which a similar version was implemented .

Scope & Requirement

IN the 1st Phase of online attendance management, it was discussed to have the following-

Teacher Mode:

• Design a school attendance tracking app where a teacher can view the list of children assigned to them.
• Children will be attending multiple lectures in a day.
• The teacher needs to check-in and out after each of the lectures.
• Ability to export attendance for each class or student

Student Mode/ Parent Mode

• Student / Parent should be able to see the online attendance management system
• Check the Goal vs Achieved attendance criteria
• Backend would be done via mass upload at the Go live date by the admin to upload all Student, Teachers and Subject schedule with the timings.

Implementation

Technology and Architecture

Technology

• The web app was deployed with the below technological component
• Backend Code: .NET Core, C#, Node.js
• Mobile App code: React Native
• Web App code: ReactJS
• Database: SQL Server, MongoDB
• Cloud: Microsoft Azure

Integrations

• Migration from an on-premise database to Online Student, Teacher, Subject database
• Single Sign-on using Auth0
• Sendgrid

Security:

• Data Encryption
• Multi-Factor Authentication for Admin, Teacher, and students when logging in
• All API endpoints are tokenized

Backup and Recovery

Cloud systems and components being used are secure and with 99.99% SLA. We have added HA/DR mechanism to create a replica of the services

Scalability

Application is designed to scale up to 10X times the average load received on the 1st 6 months of its usage and all cloud resources are configured for autoscaling based on the load

Cost Optimization

Alerts and notifications are configured to notify if the budget is being exceeded. Peritos being a cloud partner is managing the environment for the client by keeping a close watch on the cost and finding ways to optimize the same

Code Management, Deployment

• Code for the app is handed over to the client through Microsoft App Center.
• CI/CD is implemented to add automatically build and deploy any code changes

Features

• Students are able to see the list of subjects and timetable at the click of mouse
• Teachers are able to see the list of subjects , classes and student’s attendance and mark daily attendance
• Students are able to view the attendance % and the minimum attendance needed vs achieved
• On the go attendance marking and calculations are updated
• Holidays and classes cancelled are incorporated in the minimum attendance calculations
• Quick setup, Dashboard view

Challenges

• Getting the huge amount of data to incorporate and add to the online database. We took an online database migration tool and added AI ML logic to ensure we could do a quick sanity testing with some test cases to be sure the app works as expected.
• Since the students and teachers were both used to the manual way of working for managing the attendance it became a huge effort to train the entire lot.
• The app we developed was simple enough to use so just with a 15 min basic tutorial and training the teacher and super users we were able to achieve this within an 8 working today time frame.

Support

As part of the project implementation we provided 1 month of extended support. This includes any major / Minor bug fixes.

Next Phase

We are now looking at the next phase of the project which involves:

• Ongoing Support and adding new features every Quarter with minor bug fixes
• Web based module to have admin be able to mass Upload teacher, students rolled out for the backend staff