A small startup takes on Big Tech’s AI hiring promises, and just might be doing it better.

If you're a founder, investor, or recruiter paying attention to the job market lately, you’ve probably noticed the same thing: the resume still rules. Despite endless chatter about portfolios, GitHub stars, and TikTok resumes, recruiters are still opening PDFs. Still scanning for bullet points. Still judging by formatting.

And yet, a quiet rebellion is brewing, not in the offices of Google or Meta, but in a lean startup called InterviewPal.

Earlier this month, they launched something called Resume Reviews. Sounds tame. Almost underwhelming. But peel back the name and you’ll find something more interesting: a proprietary AI model designed to do what most so-called “AI resume checkers” have been bluffing for years. Actually review resumes. Not keyword-match them. Not reformat them. Review them.

The startup says it gives feedback like a real recruiter. Not just: “Add action verbs.” But: “Your experience in logistics isn’t clearly tied to project outcomes — here’s what’s missing.”

It doesn’t try to make your resume look like everyone else’s. It tries to make it better.

And it’s already raising eyebrows.

Is there room for new models?

“Frankly, most resume tools are smoke and mirrors,” says an ex-HR lead at a Fortune 500 company who now consults with AI hiring startups. “They repackage templates, spit out surface-level advice, and pretend it’s intelligence. It’s not.”

What InterviewPal is attempting, and this is where it gets interesting, isn’t a wrapper on OpenAI. Their Resume Reviews runs on their own fine-tuned model, trained on tens of thousands of anonymized resumes and recruiter feedback loops. It’s designed to mimic how real hiring managers think. Not how ChatGPT thinks.

Why does that matter?

Because AI hiring has a trust problem. Candidates don’t trust black-box systems. Recruiters don’t trust automated shortlists. And investors are starting to wonder if Big Tech’s hiring algorithms are helping or hurting.

“Google’s ATS still misses top candidates because they don’t use the right buzzwords,” says one startup founder who builds AI infrastructure for talent platforms. “The problem isn’t solved. It’s automated dysfunction.”

Which raises the question: can small, vertical-focused AI startups — like InterviewPal — actually solve what Big Tech keeps fumbling?

David vs. the résumé-scanning Goliaths

It’s not just about tech.

It’s about who is building it.

Big Tech has the resources. But their models are generalist. Trained on billions of tokens, across all domains. Powerful, sure. But not necessarily helpful when it comes to career-switching sales managers or underemployed grads with three jobs on one page.

InterviewPal is betting that small, task-specific models will win here. Like how Grammarly dominated spellcheck. Or how Figma took on Adobe.

“We didn’t want to create a resume writer,” says one of the co-founders, who previously worked on speech tech. “We wanted to simulate that 10-minute call where a recruiter tells you the brutal truth.”

So far, users seem to appreciate the honesty.

Brutal, but useful

The tool doesn’t flatter. It calls out vague experience. Suggests tighter outcomes. Recommends deletions. It’s not a cover letter fluffer — it’s a resume assassin.

“Some people get offended,” the founder admits. “But we’d rather they be offended now than ghosted later.”

The product gives line-by-line feedback in seconds. It flags clichés. Points out redundancy. It also gives a score — but unlike gamified resume tools that make everyone feel like a gold-star student, the scores here are tougher to crack.

What it’s not doing: ranking you on a mystical algorithm. There’s no hidden ATS score voodoo. Just a brutally practical breakdown of what hiring managers want to see.

And unlike most career tools, this one doesn’t push upsells mid-process. No paywalls mid-review. The freemium model is clear — free basic reviews, pay for deeper breakdowns and coaching.

So… is it working?

Depends how you define success.

The company reports nearly $300 in monthly recurring revenue, which sounds tiny — until you realize they only soft-launched and haven’t spent on ads. Most users come from Reddit threads, Discord groups, or word-of-mouth. Many are first-gen job seekers or professionals outside the US.

And while those numbers wouldn’t excite a VC looking for the next Rippling, they do suggest traction.

Plus, it’s cheap to run. No need for 100 GPUs. No massive API bills. Just a focused model, some clever backend tooling, and a clear mission.

“People are burned out on hype,” says one early user. “This tool actually told me something new. Something real. Not just fluff like ‘make sure it’s one page.’ I’ve heard that for 10 years.”

One early-stage investor we spoke with (who asked not to be named) said they’ve been watching the team for a while: “They have product intuition. And they’re not trying to boil the ocean. That’s refreshing.”

The bigger play

Here’s where it gets more speculative.

Resume Reviews is just one piece of what InterviewPal’s building. Their suite includes a cover letter generator, an AI interview coach, and a job description analysis tool. Together, it’s starting to look less like a feature set — and more like a platform.

Think: The human layer for the job economy.

They’re not alone in chasing this. Competitors like LazyApply, Teal, and even LinkedIn itself are all expanding into job-seeker tools. But many rely on plug-and-play LLMs, and few own their data.

InterviewPal, by contrast, is sitting on what could be one of the most valuable structured datasets in hiring: labeled interview transcripts, annotated resumes, and recruiter-reviewed CVs.

If they play their cards right, that dataset alone could be licensing gold for HR tech firms or LLM labs in need of real-world hiring data.

That’s not a guarantee. But it’s a compelling angle — especially in a post-API gold rush era where everyone is hunting for vertical-specific data to differentiate.

Still, there’s reason to be cautious.

Hiring is messy. Biased. Political. A good resume doesn’t guarantee a callback. And no AI tool, no matter how polished, can fully grasp the social nuance of getting hired.

There’s also the ever-present risk of product fatigue. How many tools do job seekers really want to juggle? Can InterviewPal become the go-to — or will it become just another tab they close?

And let’s not forget: Big Tech is watching. If InterviewPal gains real traction, will the giants copy, acquire, or crush?

But for now, they’re flying just under the radar. Building quietly. Earning trust the old-fashioned way — one resume at a time.

There’s a paradox at the heart of AI hiring: the more we automate, the more human insight we crave.

Resume Reviews doesn’t try to remove the human. It tries to simulate one — the critical, experienced, brutally honest recruiter you wish you had in your corner before you hit “submit.”

It’s not a silver bullet. But it might just be a better mirror.

And in a job market full of noise, that’s worth paying attention to.