Kollectiv AI

Late one night in San Francisco, long after his kids had gone to sleep, Andrey Akselrod sat at his desk staring at a small stack of papers that had come to define his year. They were hospital bills—simple on the surface, catastrophic in practice.

The visit itself had lasted only 24 hours. The aftermath stretched to twelve months.

Insurance wouldn’t pay. The hospital wouldn’t communicate. Phone calls spiraled into new phone calls. Conflicting statements turned into collections letters. It was a bureaucratic labyrinth with no map.

For most people, the nightmare would end with frustration. But Akselrod is not most people. He is a builder—twelve years straight of nonstop startup building, from Smartling to People.ai, scaling engineering teams and automating complex global workflows. He understands systems. He understands failure modes. And this system, he realized, was failing spectacularly.

“There has to be a better way,” he kept thinking.

It would take another year, and a serendipitous reconnection, before that thought became a company.

A Partner From Another Frontier

Across the Bay, Sasha Rohachova was living a very different chapter of her career—but she, too, was growing restless.

She had built one of the first augmented reality “virtual tattoo try-on” apps, Inkhunter, which exploded to 16 million downloads. She had led frontier AI and visual discovery teams at Pinterest, piloting 0-to-1 products in machine learning and computer vision. She spent her days immersed in innovation—yet she felt increasingly pulled toward a different challenge.

“I’ve always been unafraid of unfamiliar territory,” she says. “I started my AR company before I owned a smartphone. I moved to the U.S. before I knew how to speak English well. What matters is curiosity. What’s broken? What’s possible?”

One afternoon, a mutual investor reached out.
“You should talk to Andrey,” he told her. “Your skill sets might fit together.”

They reconnected. Talk turned into exploration. Exploration turned into alignment. They sat down with a “co-founder prenup,” the brutal list of questions every founding team should answer but almost never does. Ambition. Values. Conflict. Vision.

They matched.

But the partnership still needed a problem—one big enough to carry a decade of work.

Into the Back Office

The founders started sampling industries. Finance. Logistics. Consumer software. But nothing clicked until they stepped into the fluorescent-lit back rooms of dental practices.

If the hospital billing system was broken, dentistry’s was positively prehistoric.

Rohachova remembers shadowing billers for days.

“I was shocked,” she says. “Copy-pasting. Sitting on hold with insurance companies. Manually re-submitting claims. Hundreds of tiny workflows stitched together by human effort.”

The software was outdated. The processes were brittle. The labor inefficiencies were staggering. And most importantly—the pain was universal.

The founders interviewed hundreds of people: dentists, billing managers, RCM specialists. They sat silently in offices, mapping real-world workflows from the inside out. At one point, they even tried doing the work themselves.

“We needed to know where the pain lived,” Rohachova says. “And whether people would pay to eliminate it.”

They quickly learned something surprising: dental practices weren’t asking for AI. In many cases, they didn’t even have the vocabulary for it. What they were asking for was relief.

Building the Administrative Engine of the Future

Kollectiv AI was born from a simple but radical premise:

AI shouldn’t just recommend actions. It should take them.

This is the essence of agentic AI—software that performs work, not just produces output. And for dental revenue cycle management, the fit was uncanny.

Akselrod paints the picture:

“Insurance verification, claim filing, denial management, appeals, payment posting—it’s a chain of dozens of steps. If a human misses one, revenue is lost. An AI agent doesn’t miss steps.”

Kollectiv’s system logs into insurance portals, extracts benefits, checks claim statuses, identifies denials, writes appeals, posts payments, and reconciles accounts—autonomously.

It doesn’t ask. It acts.

It doesn’t fatigue. It improves.

And it doesn’t replace dental staff—it frees them.

“People don’t become dental assistants to spend their day on hold with insurance companies,” Rohachova says. “AI elevates their work. It removes the drudgery so humans can be humans again.”

Trust, Not Speed

But Akselrod knew something from the beginning: healthcare is not a place for Silicon Valley’s reckless mantra of “move fast and break things.”

“We handle sensitive patient information,” he says. “You don’t earn trust with slogans. You earn it with architecture.”

Every piece of Kollectiv’s platform is built with HIPAA compliance at the core: encrypted data flows, least-privilege access, audit trails, human-in-the-loop overrides, and explainability at every step.

AI doesn’t go unchecked. It escalates edge cases. It documents why it took each action. And ultimately, it becomes more trustworthy because it embraces supervision rather than dodging it.

The North Star: Fewer Interventions

While most companies measure ARR or customer growth, Kollectiv tracks something different: interventions.

It’s a metric borrowed from autonomous vehicles.
How often does the system need a human to take over?

Rohachova puts it simply:
“Our goal is true autonomy. The fewer interventions required, the closer we are.”

The company has already signed partnerships covering 100+ dental locations, including two dental groups generating $30–50 million in annual revenue. Pilot results suggest the platform is already faster—and more precise—than human teams.

But the founders are not rushing.

“This is a marathon,” Akselrod says. “We want the administrative engine of dentistry to run flawlessly. That takes time, rigor, and trust.”

The Future Is Administrative

If Kollectiv AI succeeds, the transformation won’t look futuristic. It will look almost invisible.

Patients won’t see AI agents behind the scenes verifying their insurance instantly.
Dentists won’t see AI resolving claim denials while they’re treating patients.
Office staff won’t see AI updating payment ledgers late at night.

But they will feel it:
Cleaner operations. Faster collections. Fewer headaches. More time with patients.

When the administrative engine runs itself, the care improves itself.

And maybe, one day, no one will spend a year fighting over a 24-hour hospital bill.