AI Integration · Hiring workflows

See who is
a fit for the role.

Paste a job description in any major language, upload a candidate resume, and get an instant 0-100 fit score with the specific strengths, gaps, and 3 sharp interview questions to bring into the loop. Same shape we build into hiring setups: an AI layer that reads real candidates against your real rubric, wired into your ATS or applied over your existing pipeline.

See the live demo Build one for your team
AI Resume Screener

Score any resume against any job description.

Job description

Candidate resume

Typically 5–8 seconds. Works in any major language: English, Hindi, Spanish, French & more. Nothing is stored on our side. Try it freely.
0fit score

Verdict

,

Strengths

    Gaps & Risks

      Suggested interview questions

        The Impact

        What AI-integrated hiring
        looks like in practice.

        Tell us your hiring stack

        Per resume, every time

        Score, strengths, gaps, and interview questions in one pass. No clicking through tabs, no re-reading the same PDF three times.

        Multilingual out of the box

        Job descriptions and resumes in any major language: English, Hindi, Spanish, French, and more. Works on mixed-language pairs too.

        Hours saved per recruiter, per week

        Triage hundreds of resumes in minutes. Recruiters focus on the shortlist, not the slush pile.

        Tuned to your hiring bar

        Must-haves, nice-to-haves, dealbreakers, seniority bands: codified once and applied consistently across every candidate.

        Inside this build

        The integration layer that makes AI usable on real resumes.
        The same building blocks power yours.

        The demo above runs the same pipeline that scales into a production hiring build. The model itself is a commodity; the value is in the pipeline wrapped around it.

        PDF / DOCX parsing

        Drop in the resume the candidate sent. We extract the text and feed it straight to the model. No copy-paste needed, no format wrangling.

        Instant fit score

        A 0-100 score that weighs must-haves against nice-to-haves. Colour-coded so you can triage a pile of resumes in seconds.

        Strengths, made specific

        Cites named technologies, real years of experience, and delivered projects from the resume itself. No generic praise, no hedging.

        Gaps and risks, called out

        Honest weaknesses and red flags against the role's bar: seniority mismatches, missing must-have skills, project-shape risk.

        Sharp interview questions

        Three questions you can paste into the screening loop, designed to probe gaps and pressure-test claimed strengths.

        API or in-product

        Run as a standalone tool, or plug it into your existing hiring system as a first-pass step before a human ever opens the file.

        How we build it

        4 steps from a JD and a resume
        to a structured hiring signal.

        The pipeline the demo above runs on. The same pipeline scales into a production build tuned to your rubric and wired to your ATS.

        01

        Paste the job description

        The whole role description: responsibilities, must-haves, nice-to-haves, seniority. The richer, the better the read.

        Try the screener
        02

        Drop the resume

        PDF, DOCX, or pasted text. Up to 5 MB. We pull the text out automatically, no format wrangling on your side.

        03

        AI scores it

        The model assesses fit on must-haves and nice-to-haves, then writes specific strengths, gaps, and interview questions.

        04

        You decide

        A glance at the fit score and gaps tells you whether to advance, reject, or send for a deeper read.

        Frequently Asked Questions

        Is this a product we can subscribe to?
        No. What you see here is a live demo of an AI hiring layer. A production build is delivered to you as software you own, running on your framework. Same building blocks, tuned to your rubric, integrated into your ATS. No monthly seat fees to a vendor.
        How reliable is the fit score?
        Directional, not decisive. 75+ means the candidate clears the JD bar and is worth a real read. Under 40 means the JD's must-haves are not there. The verdict paragraph and the gap list are usually more useful than the number itself for a recruiter deciding next steps.
        Is it safe to run real candidate data through the demo?
        The demo has no database and does not log the JD, resume text, candidate name, or output. Content is passed to the AI vendor over their enterprise API (no training use), the result comes back to your browser, and it ends there. For production, a real build can run under zero-retention terms with a commercial vendor or on a self-hosted open model inside your VPC, depending on how strict your compliance bar is.
        Which resume formats work?
        PDF, DOCX, and plain text up to 5 MB. The PDF must have real selectable text (not a scan). If a scanned PDF fails, switch to the paste-text option. Production builds add OCR for scanned resumes and can ingest attachments straight from Gmail, Google Drive, or your ATS.
        What does a real hiring-AI integration look like?
        The AI slots in as a first-pass step inside your existing hiring pipeline. Candidate applies to a role in your ATS (Greenhouse, Lever, Ashby, Workable, Zoho Recruit, Bamboo). The AI reads the JD + attached resume, writes fit score + strengths + gaps + suggested questions back onto the candidate record. Recruiter sees it in their normal tool. No new dashboard, no new login.
        How long until it goes live?
        A first working slice, tuned to one role family and one ATS, typically goes live once scope is agreed. From there, additional role families, deeper rubric logic, take-home graders, and recruiter copilots layer on once you have proof from real screenings.
        Does it work outside English?
        Yes. English variants (US, UK, Indian), Hindi, Spanish, French, German, Portuguese, Arabic, Mandarin, and most major European and Asian languages produce sharp output. Verdict, strengths, gaps, and interview questions come back in the JD's language so recruiters read them natively.
        What if the JD and resume are in different languages?
        Common and handled natively. English JD + Hindi resume, Spanish JD + English resume, Arabic JD + French resume: the model reads each document in its own language, then writes the assessment in the JD's language. Useful when you hire across regions where candidate resumes rarely match the JD's language.
        Where does the data go?
        For the demo: to the AI vendor's enterprise API (no training use, brief abuse logs then deleted) and back to your browser. Nothing lands in our DB. For a production build you pick: enterprise API, the same vendor under a zero-retention contract, or a self-hosted open-weights model running fully inside your infrastructure so resumes never leave your VPC.
        Can we tune the rubric ourselves?
        Yes. The rubric is configuration, not code. Must-haves, dealbreakers, nice-to-haves, seniority bands: your recruiters edit them from an admin panel. When your hiring bar shifts or you open a new role family, the logic updates without a rebuild.
        Which roles benefit most?
        Roles where the JD lists concrete skills and a clear seniority: engineering, data, product, design, marketing, sales, recruiting, customer success, support. Less useful for roles where fit is mostly chemistry and judgment (top executive search, senior partnerships), where a first human read is still the right first step.
        How do you handle bias?
        The screener follows the JD. Fairness starts with a JD that describes what people can do, not who they are: real years of experience over pedigree fields, demonstrated outcomes over school names. Age, gender, race, religion never enter scoring. No AI removes bias entirely, so this stays a first-pass filter, not a hiring decision.
        Can Entexis build this for us?
        Yes. This is what we do. Hire us on Upwork and we will scope your first role family, encode your hiring rubric, integrate the screener into your ATS (Greenhouse, Lever, Ashby, Workable, HubSpot), and get a working first slice live once scope is agreed. You own the code, the model runs where you choose, and candidate data stays on your infrastructure. Look for us at upwork.com/agencies/entexis.
        Entexis Labs · Live demos

        Try the AI workflows we build, right now.

        Same workflow patterns Entexis rolls into client setups. Try them in your browser, no signup. If one feels like it'd help your team, we build a private version tuned to your data.

        AI on Your Own Data
        Compare generic ChatGPT with AI grounded on your data, rules, and workflow.
        Try the demo →
        AI Competitor Analyzer
        Paste 2 or 3 product URLs and get a side-by-side comparison with a verdict and follow-up Q&A.
        Try the demo →
        AI Document Q&A
        Upload a PDF or Word doc, ask questions, get grounded answers with quoted lines from the file.
        Try the demo →
        AI Contract Intelligence
        Drop a contract, get ranked risks with quoted clauses, obligations, and questions to ask.
        Try the demo →
        Custom AI Workflows
        Any input in, any output back. Live example: paste any page URL and get AI-generated images with regenerate and download per slot.
        Try the demo →
        AI Business Accounting
        Rules-driven AR queue with expected cash-in, drafts, and escalations.
        Try the demo →
        AI Voice Agent
        A live AI receptionist that answers calls and books appointments end-to-end, multilingual.
        Try the demo →
        SEO / GEO / AEO Checker
        Paste any URL and see how it scores for Google, ChatGPT, and voice search. Free, no signup.
        Try the demo →
        AI-Integrated Hiring · Production-ready

        Custom hiring AI, wired into your framework.

        The screener above is one shape. We also build take-home graders, recruiter copilots, candidate-engagement bots, and ATS-integrated triage systems, tuned to your rubric and the languages you hire across. First working slice quickly, on your infrastructure.

        12+
        Years
        5
        Continents
        2,100+
        Engagements
        Looking for similar solutions?

        Hire Entexis on Upwork.

        See our track record, client reviews, and completed AI projects. Reach out from the platform and we will scope your first hiring build.

        Hire us on Upwork → View our Upwork profile

        Built end-to-end by Entexis. Reply within one business day.