Prepverse
Get Hired Faster with Prepverse AI
83 followers
Get Hired Faster with Prepverse AI
83 followers
Experience realistic interviews with Prepverse's adaptive AI that provides real-time feedback and personalizes questions based on your responses.
This is the 3rd launch from Prepverse. View more
Personalized Job Search
Launched this week
Spending 10hrs/week doom-scrolling job boards? No cap, that's cooked. π
PrepVerse's AI agent literally does the job hunting FOR you β upload your resume, set your vibe (role, location, salary), and wake up to a daily feed of jobs that actually match your profile. No fluff, no irrelevant listings, just your roles.
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50+ platforms scanned daily
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94% resume match accuracy
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Live match scores on every card
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Morning digest dropped straight to your inbox
Stop the grind. Let the AI cook. π₯
Free Options
Launch Team
Congrats on launching. The job search was a struggle for me, and is only getting harder for people right now. The adaptive questions that adjust based on your answers is such a smart touch. Generic interview prep never actually mirrors how a real conversation will go. Does the AI tailor questions specifically to the role and industry you're applying for, or is it more organized?
@aya_vlasoffΒ Thank you, means a lot β especially hearing it from someone who's lived the struggle firsthand.
Quick clarification though - this particular launch is our Personalized Job Search agent (the one that scans 50+ platforms and matches roles to your resume daily). The adaptive interview prep you're describing is actually a separate Prepverse feature! glad it's making an impression too! π
But since you brought it up! yes, the interview module does tailor questions to the specific role and industry, not just a generic question bank. It pulls context from the JD you're applying to and adjusts the difficulty and domain of questions as the session progresses. So a PM role at a fintech gets a very different question flow than a SDE role at a product startup.
And you're 100% right that generic prep doesn't mirror real conversations β that's exactly why we built the adaptive layer. Prepverse interviews are dynamic, not scripted.
If you haven't tried the job search side yet though drop your resume in, curious what match scores you'd see for roles you're actually targeting. π―
The job search agent part is what got me! I know so many people (including myself) who spend entire weekends just scrolling LinkedIn and somehow still miss the best roles. 50+ platforms scanned daily with a match score is way better than doing it manually. How does it handle roles that don't have a clear title? Like if someone is looking for a hybrid marketing/product role, does it pick up on those cross-functional listings or does it mainly match on job title keywords?
@yotam_dahanΒ First of all, Thanks for checking out the product.
Most job matching tools do naive keyword matching on job titles, which completely falls apart for cross-functional roles. We handle this differently.
Instead of matching on title, our agent embeds both the job description and the user's resume into a semantic vector space! so a listing titled "Growth & Product Strategist" or even just "Generalist" still surfaces if the JD's underlying skill requirements overlap with the candidate's profile. The match score reflects semantic similarity across skills, responsibilities, and context, not just title keywords.
For hybrid roles specifically (marketing/product is a great example), we actually see this as an edge case where we outperform manual search because most people wouldn't even know what keyword to type to find those listings. Our embeddings catch the signal even when the title is ambiguous.
That said, we're still improving edge cases around very niche cross-functional roles.
From the hiring side in Europe β LinkedIn is a given, but a lot of strong candidates sit on local boards that major aggregators tend to ignore. Any plans to expand beyond English-speaking markets?
@klara_minarikovaΒ Thanks for checking out the product π
Really valid point and honestly one of the gaps we're actively thinking about.
Right now our agent is optimized for the Indian market β platforms like Naukri, Internshala, Instahyre, Wellfound India where the problem of fragmented job boards is especially acute for freshers. That's our beachhead.
But the underlying architecture is platform-agnostic. Our scraping and ingestion layer treats each job board as a pluggable source adding a new platform is largely a config + parser problem, not a core engineering rewrite. So expanding to regional European boards is technically feasible without rebuilding from scratch.
The harder problem you're pointing at is actually multilingual semantic matching β making sure a CV written in English matches correctly against a JD written in French or German. We haven't cracked that yet, and I'd rather be honest about it than oversell. It's on the roadmap but needs proper multilingual embedding models, not just translation layers.
If you're seeing strong candidate pools sitting on specific local boards in your region, I'd genuinely love to know which ones β that kind of ground-truth signal from the hiring side is gold for us right now. π