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    AI-Powered Resume Screening Dashboard

    Upload thousands of resumes in bulk and let AI automatically extract candidate information, standardize profiles, and categorize applicants into qualified, review-needed, and incomplete groups, reducing manual screening time by up to 80%.

    Book An Appointment
    80% Reduction in screening time
    Drop resumes here
    or click to upload a ZIP folder
    Resume_Daniel_Wilson.pdf Resume_Ryan_Mitchell.docx Resume_David_Thompson.pdf Resume_James_Anderson.pdf Resume_Michael_Carter.docx
    Extracting New_Resumes.zip
    Unpacking and reading 1000 resumes from the folder
    0% Extracting
    Unzipping folder…
    Summary 0 + Resumes Uploaded
    New Candidate
    Successfully Uploaded
    0
    0%
    Daniel Wilson Ryan Mitchell David Thompson Sara Khan Omar Farooq Priya Sharma Ethan Brooks Ayesha Malik Zara Ali Hina Raza
    Needs Review
    Information Missing
    0
    0%
    James Anderson Usman Tariq Bilal Ahmed Fatima Noor Amit Verma Karan Mehta Divya Rao John Paul
    Not Sure
    Profile Incomplete
    0
    0%
    Michael Carter Neha Kapoor Arjun Singh Meera Iyer Rohan Gupta Anjali Desai
    Recruiter Problems

    Challenges Faced Before Implementing the AI Recruitment Platform

    Recruiters faced multiple operational challenges that slowed hiring, reduced candidate visibility, and made it difficult to identify and engage qualified talent efficiently.

    01

    Time-Consuming Resume Processing

    Recruiters were spending 4 to 6 hours daily opening resumes one by one, copying data into spreadsheets, and manually building candidate profiles. The process was slow, inconsistent, and exhausting.

    02

    Inconsistent Screening Process

    Different recruiters extracted different information from the same resume. There was no standard format, which made comparing candidates across the team nearly impossible and led to inconsistent shortlisting decisions.

    03

    Keyword-Based Search Limitations

    Qualified candidates were being missed because keyword-based search in their old system only matched exact text. A resume that said “JS developer” would not surface when searching for “JavaScript engineer.”

    04

    Difficulty Reusing Past Applicants

    When a new role opened, the team had no way to re-use past applicants. Old resumes were buried in email folders or local drives, making every new hire feel like starting from scratch even when suitable candidates already existed.

    Solution We Delivered

    We built a production-ready AI-powered resume parsing and candidate screening platform that transforms how recruiting teams handle high-volume hiring. The solution centralizes resume ingestion, AI-based data extraction, candidate profile management, job description matching, and talent database search into a single easy-to-use dashboard. Recruiters can upload batches of hundreds of resumes simultaneously, review structured candidate profiles within seconds, and manage their entire candidate pipeline from one place without switching between tools.

    ResumeRead
    Candidates Fields Analytics

    Create New AI Extraction Field

    Field Name
    Notice Period
    Field Type
    Text
    Description for AI
    "Extract how many days or weeks before the candidate can join a new company."
    Required
    Apply to future resumes
    Apply to existing parsed resumes
    AI

    Extract the recruiter-defined field "Notice Period" from every uploaded resume.

    Queue
    James_Anderson.pdf
    Michael_Carter.docx
    Daniel_Wilson.pdf
    Ethan_Brooks.pdf
    Ryan_Mitchell.docx
    David_Thompson.pdf
    Updated
    Waiting for the field to be created…

    ATS Candidate Database

    0 / 6 updated
    CandidateNotice PeriodEmployment Gap
    James Anderson——
    Michael Carter——
    Daniel Wilson——
    Ethan Brooks——
    Ryan Mitchell——
    David Thompson——

    Powerful AI Features for Smarter Hiring

    Every feature in this platform was built to simplify recruitment. By automating resume parsing, candidate data extraction, and intelligent job matching, the platform reduces manual effort and empowers recruiters to spend more time engaging with qualified candidates and making better hiring decisions.

    ResumeRead
    Candidates Fields Analytics

    Find The Right Candidate

    Job Description
    Recruiter Brief
    50% Weight
    Hiring Preferences 5 × 10% weight
    10%
    10%
    10%
    10%
    10%
    AI

    Extract Immediate Joiner, Under Budget, Location, Experience and Communication criteria from bulk resume.

    Matching candidates to your job description and hiring preferences.
    Scoring every resume with a 50% job-fit score and five weighted hiring preferences (10% each).
    0% Complete

    Top 20 Matching Candidates

    0 / 20 searched
    CANDIDATEMATCH SCOREDOWNLOAD
    Number of Candidate
    (16)
    Number of Candidate
    (18)
    Number of Candidate
    (12)
    Number of Candidate
    (15)
    Number of Candidate
    (10)

    Tech Stack Used for Blackstone

    • Frontend
    • Backend
    • API Integration
    • Database
    • Hosting
    React JS

    React JS

    Langchain

    LangChain

    Langgraph

    LangGraph

    claud

    Claude

    LLM

    LLM

    Agentic AI

    Agentic AI

    Prompt Engineering

    Prompt Engineering

    Postgres

    Postgres

    aws

    Hostinger

    Vineet Choudhary

    August 6, 2026

    1:22 pm

    No Comments

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