For years, the hiring process has been sold as a problem technology could solve. Better applicant tracking systems, smarter filters, automated screening, and AI-powered workflows were all supposed to make it easier for employers to find the right people and for candidates to get noticed.
Instead, many companies are now dealing with the opposite outcome. Hiring teams are overwhelmed with applications, candidates feel invisible, and the traditional resume is becoming less useful as a meaningful signal. In that environment, Talvy founder KJ Hardrict believes the real issue is not a shortage of talent. It is a breakdown in how people are being seen.
That is the premise behind Talvy, the Cambridge-based startup building a more human, video-first professional profile designed to help employers identify strong candidates based on traits that rarely fit neatly into a PDF. Hardrict’s argument is simple. Hiring managers and applicants are both frustrated by the same system, and both sides are telling the same story in different language.
“I’m talking to hiring managers, leaders of companies, founders, and they’re like, man, I can’t find great people,” Hardrict said. “Then on the applicant side, it’s like, I’m trying to apply literally everywhere, but no one’s giving me a chance. If both sides are complaining about fundamentally the same problem, there’s really a systemic problem happening here.”
That insight pushed Hardrict and his team to go all in on rethinking the hiring process from the ground up.
A hiring market flooded with noise
Talvy enters the market at a moment of unusual tension. White-collar workers are increasingly expected to be AI-native. Job seekers are using large language models to rewrite resumes, optimize cover letters, and auto-apply to roles at scale. Employers, meanwhile, are receiving far more applications than they can reasonably review.
According to Hardrict, that has changed the basic economics of recruiting. The problem is no longer access to applicants. It is signal quality.
He says many companies are effectively ignoring inbound applications altogether, not because they are hiring less, but because the sheer volume has made it too difficult to separate strong candidates from AI-polished noise. In many cases, companies are leaning more heavily on referrals, sourcing, and recruiters just to identify people worth talking to.
“There’s a mass amount of applications coming in, in due to a large part of the AI tools that are auto applying on the other side,” Hardrict said. “You can make sure a resume matches those screening processes. So then they just ignore them.”
That creates a strange contradiction in the market. Employers say they cannot find the right people, even as they are inundated with applicants. Candidates, meanwhile, keep applying but feel like nobody is actually seeing them. Hardrict believes traditional hiring infrastructure has become too easy to game and too shallow to trust.
Beyond the resume
It is tempting to describe Talvy as a startup for video resumes, or even as a TikTok-style layer for hiring. Hardrict understands the comparison, but says it misses the deeper ambition behind the product.
For him, the problem with the resume is not just format. It is comparability. Two candidates for the same role may describe themselves in completely different ways. One may focus on technical tools. Another may emphasize leadership experience. A third may talk about cross-functional collaboration. Each may be telling a true story, but none of them are telling it on the same axis.
That makes hiring harder, not easier.
“We realized that even just a software engineer, one could talk about the coding languages they learned, another one could talk about the amount of people on the team that they led, the other one talked about how many cross-functions they were a part of,” Hardrict said. “When you’re trying to compare those three, they’re not on the same axis.”
That insight shaped Talvy’s product philosophy. Hardrict says the platform is built around fairness, structure, and richer context. Candidates do not just upload a video and hope it works. They are guided through prompts designed around five core axes: craft, mindset, growth, purpose, and connection. The goal is to create what Talvy calls human-centric data, a more nuanced picture of who someone is, how they think, and what they may be like to work with.
In that sense, video is not the gimmick. It is simply the most information-dense medium Talvy found for capturing qualities employers increasingly care about but struggle to measure through traditional applications.
“People are really indexing on someone that’s trustworthy, has grit, has intrinsic motivation, is willing to put in the work,” Hardrict said. “And then there’s also the extra aspect of, would I want to have lunch with this person? The vibe and culture of the company is becoming really important.”
Using AI carefully
Even though Talvy is building in the age of AI, Hardrict is careful not to present the platform as a tool for manufacturing polished candidates. In fact, much of his thinking centers on the opposite idea.
He sees a fine line between using AI to understand someone and using AI to put words in their mouth.
Talvy uses AI to parse resumes, interpret stories, analyze patterns, and help employers search for people using natural language. But Hardrict says the system is not meant to overwrite or sanitize what makes a candidate human. Instead, the goal is to understand the person more holistically across all available inputs and make that understanding queryable on the employer side.
“We don’t want to put words in your mouth,” he said. “Our whole job with AI is to understand someone as a human holistically, whether that’s their experiences, their human stories and their links and whatever. We just understand them holistically.”
In practical terms, that means Talvy is not matching a person to a job description in the conventional sense. It is matching human profiles to employer queries. A company might search for a technical candidate who is charismatic, resilient, and shaped by a meaningful life challenge. Talvy’s system then surfaces people whose profiles align with that description, rather than simply looking for keyword overlap between resumes and requisitions.
That distinction matters. Hardrict believes too much hiring tech still revolves around flattening people into checklists. Talvy is trying to preserve individuality while making it easier to identify fit.
Early days, clear conviction
Talvy is still in its early stages. Hardrict was direct about that. At the time of the interview, the company had launched just over a week earlier and had not yet placed anyone into a new job through the platform.
“So for the sheer number of landing people jobs, that’s zero as of today,” he said.
But he framed that not as a setback, but as part of the company’s first validation stage. The immediate priority was proving that candidates would actually be willing to create profiles, especially in fields like engineering where people may feel less comfortable on camera.
That was the first side of the marketplace to unlock. The second is giving employers tools they can immediately use.
Hardrict said Talvy is preparing features that will let employers shortlist candidates, review profiles more efficiently, and build private or public groups for different hiring and networking contexts. The company has identified a first set of startup roles to support, including engineering, sales engineering, go-to-market, and operations positions. The near-term bet is that smaller companies without full ATS workflows may be especially eager for a faster, more human way to evaluate candidates.
The long-term ambition is much larger. Hardrict envisions a world in which people build one persistent Talvy profile and opportunities come to them, rather than repeatedly applying into black-box systems.
“We’re on the applicant’s side to try to make it so they never have to apply to another job again,” he said. “Make your Talvy profile and we’ll help land you opportunities.”
A more optimistic vision for job seekers
Hardrict described the hiring market as dominated by doom and gloom, a landscape where many applicants assume they are shouting into the void. His pitch is not that Talvy magically solves every problem overnight. It is that candidates deserve a better chance to be seen, and that companies need a better way to recognize potential before it disappears inside application systems.
“I’m trying to make it a little bit more positive,” he said. “At least give them a chance. We’ll give you a chance to be seen.”
That optimism may be one of Talvy’s real differentiators. Plenty of startups are building AI tools for hiring, screening, and workflow automation. Fewer are trying to make the process feel more human at the exact moment it is becoming more automated.
Hardrict seems to understand that paradox clearly. The more AI compresses technical skill gaps and standardizes application materials, the more other traits begin to matter. Trust. Grit. Curiosity. Story. Presence. The things that are hard to automate may become the things that matter most.
Talvy is betting that the next generation of hiring infrastructure will have to reflect that reality.
Whether the company becomes a mainstream hiring platform or remains a niche tool for more forward-looking employers, the premise is already resonating because it starts from a truth many people on both sides of the market already feel. The current system is producing more data, more automation, and more applications, but not necessarily more understanding.
Hardrict’s answer is not to remove technology from the process. It is to use it more thoughtfully, in service of helping people be seen as people again.
