The hiring ecosystem has long been a maze of incompatible systems. Every large employer uses a different Applicant Tracking System and in fact more than 98% of Fortune-500 firms now depend on such systems for hiring, each with its own forms, validations, and access rules. For job boards and candidates alike, this creates a fundamental inefficiency: the same information must be entered again and again through outdated systems that can barely talk to one another.
Enter Cornelius Renken, Technical Product Leader for AI Applications at Kombo, an HR technology company redefining how applications move through digital infrastructure. Renken leads one of the most ambitious projects in applied artificial intelligence, an automation platform that enables AI agents to submit job applications autonomously across any ATS system in the world. His perspective on reliability is grounded not only by his product work but also in his role as a judge for the Globee Awards for Impact.
“Applying for a job shouldn’t feel like manual data entry,” Renken says. “We’re building AI that can interact with any form, any validation rule, any CAPTCHA, just like a human would, but faster, more reliably, and at scale.”
Building the Infrastructure of Intelligent Workflows
When Renken founded AI Apply in December 2024, it began as an experiment inside Kombo with a single developer exploring how large language models could interpret live job applications dynamically. Within months, the project had grown into the company’s first dedicated applied AI vertical, complete with a cross-functional team spanning engineering and product.
The platform now automates end-to-end job submissions into enterprise systems like Workday and iCIMS, effectively bridging one of the most fragmented gaps in modern hiring. It does this through a large language model-driven workflow that can read, interpret, and complete online application forms while handling real-world complexities such as CAPTCHAs, dynamic inputs, and corporate anti-bot measures.
“The challenge isn’t just understanding language,” Renken explains. “It’s teaching AI to behave deterministically, to fill out a form, validate its own logic, recover from an error, and do it again thousands of times a day without failing.”
To achieve that reliability, his team designed a self-healing architecture where the system continuously monitors its own progress and corrects errors in real time. They also implemented intelligent caching and context optimization, reducing model calls and bringing down LLM costs without compromising accuracy. This step was critical in making the product profitable for enterprise clients.
From Concept to Commercial Breakthrough
AI Apply has already proven transformative. The platform allows job boards to connect with enterprise employers instantly, eliminating the need for manual API credentials or custom integrations. For agencies that once absorbed high per-application costs on platforms like Indeed, automation has reduced those expenses by up to eightfold, depending on volume and workflow. Industry research shows that AI-driven recruitment automation can also reduce time-to-hire by as much as 75%, turning traditionally slow employer pipelines into near-instant submission flows.
By making job application workflows interoperable, the system also enhances the jobseeker experience. Candidates can apply once through a single interface while AI Apply handles the underlying complexity across disparate employer systems. In essence, the platform removes friction for both sides of the market, empowering job boards to innovate faster and candidates to apply smarter.
Engineering for Scale and Stability
What distinguishes AI Apply from other automation attempts is its depth of engineering discipline. Under Renken’s leadership, the team experimented with multiple agent architectures, from graph-based representations of job forms to continuously learning LLM agents and hybrid human-in-the-loop systems. Each iteration brought the platform closer to generalization, the ability to adapt to new enterprise systems without retraining or manual intervention.
“Most automation systems break the moment something changes on a website,” he says. “We wanted ours to learn contextually, to see a new field and infer its purpose the same way a human would.”
To maintain operational excellence, Renken’s team built extensive observability and telemetry tooling. Every workflow, which can last over two hours end-to-end, is tracked in real time, allowing the team to identify and resolve issues at scale. This commitment to transparency and feedback loops has been key to sustaining reliability across thousands of concurrent workflows.
Redefining Industry Standards
The implications of AI Apply extend far beyond HR tech. Its success demonstrates how AI agents can automate structured yet context-sensitive processes across industries, from supply chain logistics to financial onboarding. But in recruitment, the timing could not be more significant.
As global labor markets evolve, organizations are under pressure to scale hiring efficiently without compromising candidate experience. A 2025 market analysis reinforces this point: the global Applicant Tracking System market is already valued at approximately USD 2.7 billion and is projected to more than double over the coming decade. AI Apply positions Kombo as a pioneer in this shift, transforming how enterprise automation intersects with accessibility.
“Every improvement in the hiring infrastructure ripples across economies,” Renken notes. “If we can make applying for jobs ten times faster and eight times cheaper, we’re not just helping job boards, we’re increasing access to opportunity.”
The Future of Applied AI
Renken’s work at Kombo represents a broader inflection point in AI engineering, one where technical precision meets social utility. By proving that AI agents can navigate live enterprise systems autonomously, he and his team are setting a new benchmark for intelligent automation.
“The best AI,” he concludes, “doesn’t just predict. It performs. It acts with context, recovers from failure, and delivers outcomes we can trust.”
As AI Apply continues to evolve, its success offers a glimpse into the next generation of applied intelligence, systems that do not just analyze data but actively build bridges between humans and the technologies they rely on to work, hire, and grow.
