Vijaykant Nadadur, Co-Founder & CEO at KnowledgeVerse

Company Overview:

Vijaykant Nadadur, Co-Founder & CEO of KnowledgeVerse (K-V AI), an enterprise AI platform purpose-built to automate data-centric workflows over unstructured content—documents, reports, forms, and more. They bring together the power of LLMs, intelligent orchestration, and vertical data understanding to automate repetitive data tasks like extraction, entry, comparison, generation, and search.

Can you tell us a little about your background before starting your company?

Before founding KnowledgeVerse, I co-founded and led Stride.AI, an enterprise AI company that delivered intelligent automation solutions for global financial institutions across the US, Europe, and India. That journey exposed me to the hard truths of deploying AI in real-world enterprise environments, where scale, security, and ROI matter far more than hype.

I hold a Master’s degree in Computer Science from the University of Kentucky, where I formally studied Artificial Intelligence, well before it became mainstream. That early exposure to AI fundamentals, combined with over a decade of practical experience in product building, enterprise sales, and customer success, shaped my conviction: the real challenge isn’t AI capability, it’s making AI usable, trustworthy, and impactful inside enterprises.

This belief led directly to the founding of KnowledgeVerse, along with my co-founder Sendhil. 

How did you start your company? What were the first steps you took to get it off the ground and how did you identify the need for your product/service in the market?

KnowledgeVerse was born from lessons learned at Stride.AI. After years of implementing AI in highly regulated industries, it became clear that enterprises struggle not with AI theory, but with AI deployment.
They needed something better than an LLM playground, they needed a structured, scalable AI platform that could work across fragmented documents, siloed systems, and real-world constraints.

The first step was building our Enterprise AI Stack; a layered architecture with modular “knowledge assistants” that could handle tasks like data entry, extraction, and comparison at scale. We started by working with design partners in pharma and BFSI who had urgent document-centric workflows. These early engagements validated the need and helped us build for scale, not just experimentation.

What innovations or unique features set your company apart from others in the industry?

What makes KnowledgeVerse unique is our purpose-built Enterprise AI Stack for unstructured data.
Unlike vertical AI tools, we offer:

  • 5 specialized AI agents for document-heavy workflows: Data Entry, Extraction, Comparison, Generation, and Search
  • A preprocessing and optimization layer with innovations like semantic chunking, scoped ranking, memory hierarchy, and self-knowledge feedback loops
  • Plug-and-play workflow orchestration, allowing teams to visually build and automate document processes without code
  • Enterprise-ready infrastructure with hybrid/self-hosting support, a must-have for regulated industries

We’re not just helping clients “experiment” with AI but we help them operationalize it for regulatory compliance, knowledge management, and reporting workflows that directly impact business outcomes.

What has been the most effective strategy for scaling your business?

Our growth has been driven by a clear strategy: solve high-friction, high-impact enterprise workflows. Instead of being another AI platform vendor, we let enterprises orchestrate their specific workflows to automate painful processes like audit reporting, CAPA document generation, or policy search, to name a few.

Having already earned trust through our work at Stride.AI, we’ve been able to re-engage with many of those enterprises and scale through strong references and deep use case execution.

Another key strategy: platform modularity. Enterprises can start with a single use case and scale horizontally, activating new agents or workflows as needed. This keeps sales cycles lean and value delivery fast.

Looking ahead, what are your goals for the future of your company?

Our long-term vision is for KnowledgeVerse to become the default orchestration layer for enterprise AI workflows.
Just as ERP systems manage structured data processes, we believe AI will do the same for unstructured knowledge. Our goal is to power that future.

For entrepreneurs building in enterprise AI:

Don’t start with the tech. Start with the user’s friction. Then build systems that handle complexity, format chaos, integrations, regulatory needs and ensure you keep the experience simple. That’s how we move from demo to deployment.

Melanie Warrick, Co-Founder at Fight Health Insurance

Company Overview:


Melanie Warrick, Co-Founder of Fight Health Insurance, which helps with writing appeals to fight health insurance denial. While an appeal is not always the first step in the appeal process, they guide users through options to fight back against health insurance denials. Most health plans are required to offer internal and external appeals and while they often make it confusing, Fight Health Insurance can help.

Can you tell us a little about your background before starting your company?

My career began in film, where I was drawn to storytelling and the challenge of making sense of complex human experiences—a thread that continues to influence how I think and build. From there, I moved into consulting, managing large-scale systems and data projects across industries. Later, I made another pivot and dove into AI engineering—building machine learning features at Change.org, a deep learning platform at a YC startup, and doing both data engineering and developer advocacy for AI at Google. Most recently, I led a software engineering team implementing AI features at Virta Health that improved outcomes for patients managing diabetes. But the real drive behind joining Fight Health Insurance came from my own experience navigating the healthcare system—both as a patient and a caregiver. Supporting a parent through cancer treatment and another living with Alzheimer’s exposed just how inaccessible the process of getting care approved can be. That frustration, paired with a background in AI, health tech, and a lifelong appreciation for human stories, is what pushed me to build something better.

How did you start your company? What were the first steps you took to get it off the ground and how did you identify the need for your product/service in the market?

Holden Karau and I came together to work on Fight Health Insurance (https://fighthealthinsurance.com/)  to solve a problem we’d lived ourselves. Navigating insurance to access care is often confusing, time-consuming, and frustrating—for both patients and providers. The first step for FHI came in 2024 when my co-founder, Holden, launched Fight Health Insurance—a free tool that helps patients appeal denied claims. After a traumatic accident in 2019, it took her over six months to recover, and even with great insurance, she had to fight just to get the care she needed. As a trans woman, she’s also experienced—and witnessed in her community—the uphill battle many face in getting coverage approved. These experiences drove her to build something that could help others, and it has: thousands of patients have already used FHI, saving hundreds or even thousands of dollars in the process.

As word spread, providers began reaching out—hundreds signing up for access to a professional-grade tool. That demand led to the creation of Fight Paperwork (https://fightpaperwork.com), which I joined to help build and launch. Our AI-powered assistant is designed for healthcare professionals and staff, helping them automate the creation of prior authorization and appeal letters. Our mission is clear: improve access to care by fighting insurance AI with smarter, domain-specific AI of our own—and ultimately remove the barriers created by denials and delays.

What innovations or unique features set your company apart from others in the industry?

What sets us apart is our domain-trained generative AI, purpose-built to navigate the complexities of insurance documentation. Rather than relying on generic automation, our platform delivers context-aware letter generation, payer-specific guidance, and a natural, chat-based interface we call Doughnut. It’s fast, flexible, and designed to feel like a helpful teammate—not just another tool.

Our AI is continuously learning, improving with every interaction. It’s powered by our proprietary dataset, giving us full ownership over both our model and inference stack—no dependence on external AI vendors. This gives us a critical edge:

  • Smarter, faster iteration cycles
  • Lower inference costs
  • Efficient cloud use, reserved only for burstable workloads

We’re not just making resolving billing issues faster—we’re removing the administrative barriers that delay treatment and improving access to care at scale.

What has been the most effective strategy for scaling your business?

Our growth has been driven by real demand from the front lines of healthcare. Providers are under immense pressure—juggling 40+ prior auths a week, often with limited support and high burnout. Instead of trying to “disrupt” the system from the outside, we’ve embedded ourselves within it—building tools clinicians can use immediately to speed up their workflows and reduce time spent on billing admin. While we’re still working on streamlining integrations and onboarding, our focus has been on making the path from denied claim to submitted appeal dramatically faster.

We’re also moving in sync with the system’s evolution: new CMS regulations are pushing insurers to upgrade outdated processes, and our AI is built to scale with that shift. Our strategy is to meet providers where they are—and make sure the tech actually saves them time, reduces friction, and helps patients get care.

Looking ahead, what are your goals for the future of your company?

Looking ahead, our goal is to be the backbone of AI innovation in medical billing for providers—starting with appeals and prior auths, and expanding into other high-friction workflows. We want to empower professionals to focus on care, not paperwork. For other founders, my advice is to stay close to your users, especially in a messy industry. Build with them, not just for them. Also make sure to find the fun when you can. The journey is intense and long—so embrace the weird, laugh at the chaos, and keep your inner goof fueled. For me, it’s a bit like returning to my roots in storytelling—finding meaning, connection, and a spark of creativity even in the messiest parts of building.

Roy Mill, Co-Founder & CEO at Joshu

Company Overview:

Roy Mill, Co-Founder & CEO at Joshu helps insurance products owners configure, launch and update their products without coding through their insurance product development and distribution platform. Designed for insurance professionals and packed with features accelerating product setup, Joshu’s portals and Underwriter Desk come out of the box and support the full lifecycle of a policy.

Founded by technology experts experienced in selling insurance online, Joshu was purpose-built to give insurance professionals the tools they need to harness digital distribution and win new markets faster.

Can you tell us a little about your background before starting your company?

I am a software developer that became interested in economics and social sciences. After graduate school I became a product manager and directed a team of product managers at Ancestry.com. Then I joined a cyber insurance startup to lead product management and fell in love with insurance technology (weird, I know). That’s what brought my co-founder and me to start Joshu.


How did you start your company? What were the first steps you took to get it off the ground and how did you identify the need for your product/service in the market? 

We left At-Bay just before COVID hit. We know firsthand the pain of launching insurance products for digital underwriting and distribution, as we struggled to keep up with the needs of the “business”, given the tools that we had. So we wanted to build a new framework and a platform for how to launch insurance products without developers in the loop. COVID slowed funding, but we closed our Seed Round and made our first hire in February of 2021.

What innovations or unique features set your company apart from others in the industry?

Joshu enables non-technical insurance professionals to launch insurance products end-to-end, without a single developer involved. We’ve done it again and again, and we are able to support very different lines of business. We found a way to “containerize” insurance products, letting our clients turn insurance product specs into full underwriting and distribution operations in the shortest amount of time and the widest flexibility. The platform’s API-first architecture provides flexibility both for insurers who want ultra modern technology, and for insurers with older environments seeking a realistic path to migrate outdated and/or homegrown systems. 

What has been the most effective strategy for scaling your business?

For the business as a whole, the product is our biggest enabler of scale. While other Policy Admin Systems require significant hand-holding and professional services, ours are very limited and many of our customers are “self-driving,” meaning we can sustain many clients with very limited professional services.

For our go-to-market growth, word-of-mouth has been the best channel. We’re here for the long haul and we will tell you what we can and can’t do, building trust with our prospects, clients, and the industry.

Looking ahead, what are your goals for the future of your company?

More products launched, more premiums generated, more risk transferred and a more resilient economy and society. If we can enable that, we’ve delivered on our mission.  

Jay Patel, Co-Founder & CTO at AviaryAI

Company Overview:

Jay Patel is Co-Founder & CTO at AviaryAI, a leading provider of voice AI solutions, specializing in enterprise-grade applications for the financial and insurance sectors.

We empower businesses to automate and enhance customer interactions through advanced voice technology, seamlessly integrating with legacy systems.

Their platform enables efficient debt settlement, streamlined customer service, and improved operational workflows, ultimately driving increased efficiency and customer satisfaction.

Question: 

What is the background of AviaryAI?

Answer: 

Before AivaryAI, we were a group of co founders that started the Cambio Money App.

The Cambio Money App originally started as a NEO bank and a regular FinTech that were helping under underserved communities get access to banking, especially those that had got kicked out of the credit system through something that was check systems.

Through that process, we were trying to figure out how to get people’s credit to go up as quickly as possible.

We started with paper disputes, emails and whatnot, and then when GPT 3.5 launched, it was around the same time as those, those memes with the Presidents playing Minecraft with each other, and I was like, Wait, we can just take the voices and that whole tech and just put it on the phone and settle people’s debts that way.

And that’s kind of how AviaryAI spawned.

Before AivaryAI, we co-founded the Cambio Money App, a NEO bank for underserved communities. Inspired by GPT 3.5, we shifted to voice technology for debt settlement, leading to AivaryAI’s development

Question: 

What are some of the challenges that your team has faced in the earlier stages?

Answer: 

So the pivot was really tough because we we were trying to build the version that helped settle people’s debt in tandem with the version that aligned with enterprise, like interests.

They just could not go like work together, because the one that’s trying to settle people’s debt is honestly a little just more aggressive than what was available to the enterprise, because it’s, it’s different, right?

You’re in a negotiation mode versus, you know, trying to be a pleasant consumer facing customer service agent, right? But then, even after that, and we shut down the old company, the biggest thing was educating our users on AI.

You know, most people like when they got to play with chatgpt, most people just put something in there, treated it like Google and left right, and that’s kind of where a lot of our clients sit, and especially the people who end up actually using our software after people procure it.

It’s people that tried champion chatgpt Maybe once or twice, and now we’re giving them this agent that they have to go set up and configure and basically get it to do good work on their behalf.

So currently, our process is still super high touch, even though we have software in place that lets them do it themselves, just everyone’s so scared to do it wrong, especially because you’re making outbound calls to people you know you don’t want to ruin your brand’s reputation and whatnot.

And that’s that’s a big hurdle for them to go over. So what we do now is we have a customer success team that goes and essentially builds their first one or two for them, and then, going forward, we actually built an AI based on the notes from every previous ones of our customers that’s going to walk through and build your first couple use cases for you.

Going forward, maybe that’s going to launch in about three weeks, but yeah, the biggest thing has just been, one, after the sale, getting the actual business users to use it.

And two, once they see value, they can champion it for us to their IT teams to actually start integrating us their internal technology. 

Question: 

Can you share any memorable or defining moments that have helped shape this company?

Answer: 

When we were first building this stuff, we knew that we wanted to do something in the voice AI space, and we had that bot that was originally from the consumer app. So what we did was we went around our network, through our board, and met up with a bunch of people in a bunch of different industries.

So we went and we met up with an overflow call center, we met up with an insurance servicing call center, and we met up with both a credit union and a bank, and we basically spent time figuring out what the best thing to do in this space with our technology was.

So there was a about like a six week period of time where we were building four products simultaneous.

Simultaneously. Um, we built an auditor that basically monitored actual customer service reps scores with like, custom metrics and like a way that people can go and ask, what went wrong on this call?

What’s going wrong on all my calls? In aggregate? We built a real time translation tool.

So let’s say I was speaking in Hindi right now, and you were a customer service rep. On your screen, you would see the English version of what I was saying, and you could type it back in a clone of your own voice.

You would be sounding back to Hindi to me over the phone.

We also built what we’re building today, which is the voice agent, and then the knowledge base. So it was kind of this weird place, especially for me and the engineering team, where we were building four things, and it was like, All right, well, what’s going to get killed here, right? And then, like that, that moment where it was like, actually deciding, like, what products gonna get killed?

Because especially as you’re building, you kind of start falling in love with what you’re building a little bit. So when we finally made that decision and cut down our translator and our auditor services, it was, it was like, Oh, this is real.

And these the knowledge based product and the voice agent are, like, getting traction, and we just need to focus on that. And it just, it finally felt like things were clicking.

Question: 

What is the differentiator between AviaryAI and your competitors? 

Answer: 

There’s definitely a bunch of people in the voice AI space now, the first, but I think we were probably the first verticalized one.

And it’s really that vertical, especially insurance companies and credit unions and some banks, they are running on this really, really old software that’s really hard to integrate into and not really obvious to integrate into.

So there’s like, platforms where you can basically go and build a voice agent for yourself really easily, and, like, hook it up to a tool like everyone knows, like Calendly, but there’s no platform where you can hook up a tool to the back end banking systems of a credit union, and that’s kind of what makes us different.

We’re going to be plug and play for financial institutions and insurance companies from essentially the moment they start their IT. Teams actually begin working with us, like they work with us.

To rephrase that, they do work with us today, but like from sale to when their IT team gets our project, we have that weird in between period where we’re trying to teach the business users how to use the software in the basic state, and then we go to more advanced states.

Question: 

What kind of feedback have you received from your customers, and how does that shape your business strategy?

Answer: 

So definitely the initial gut reaction for when they try to do something, the first time, they’re just like, Oh, it can’t do all this.

Can it? And then we have to walk them through being like, No, it really can do all of this. And then when they do see it, and they finally deploy their first agent with us, and they start getting their reports back, they’re like, whoa.

This is actually just working. And there’s one of two feedbacks. Awesome.

So, how do I get more data visibility? And then two is, sometimes they go remote, remote, silent. And we always thought that was a bad thing, but they would just come back and be like, what you guys did worked well enough where we just had way too much inbound volume on things to kind of handle, handle it.

So we didn’t want to start another use case yet, but we they kept the contract right, so they’re going to start another use case once they’ve kind of figured it out, and then we have that knowledge based product too.

A big thing with that is we built this knowledge base that helps CSRS spend less time on them. The the big feedback for that one is, once people start using it and they realize they can’t basically tell an AI the tribal knowledge that they have, they kind of realize that their documentation is bad, and they go through this overhaul to make it better, and that makes our product work better with theirs too.

So like a lot of those things that you would hope it makes them reflect on, oh, we had a bad process before, and we have to make it better for our tools to work better. So we’re also now building tools to help them make their stuff better. 

Question:

What is your growth strategy? 

Answer: 

So we have two teams, obviously, me being on the technical side of the FEM team, I’m always concerned to make sure our stuff’s up to stuff. But for the most part, we are. We are either better than the majority of our competitors or competitive with the best one, right?

So it’s not that our technology isn’t there. It’s more just about, how do we make it easier for them to use now? And that kind of increases our sales velocity on like, Oh, it’s so easy to use that you don’t need to get your IT department involved, right?

So it’s a little bit hand in hand, but not really, but because our technology has gotten in such a good place over the last nine months, we’ve kind of just been like, Okay, we just need to get more people in the door. And due to the fact they’re enterprise clients, they just move a little slower.

So we just, we’re now working on, okay, even if they sign the contract and they’re in the door, and we have that as realized revenue, we we want them to be happy with the product too. So it’s like, how do we get them, even after that post buy? How do we get them going as quickly as possible? You know?

So it’s kind of go. It goes in the same way. And also just the the two industries that we’ve really targeted, they’re they’re word of mouth industry is more than like, TV advertisement or podcast advertisement industries, right?

So like, as soon as we start really showing value to a couple of them, the word spread, that’s basically what’s been happening almost every single one of our clients from the last four enterprise contracts we’ve landed had been referrals from a previous client

Question: 

What are the short term and long term goals for the company? 

Answer: 

For the short term, we kind of just want to make it as easy as possible for business users to get as far as possible without dragging their IT resources into it.

So we’re really trying to figure out how to hook directly into some of the providers specifically so they can just drop in their API key, rather than having to go through their API and I go through their IT department.

So it’s really just going from contract sign to value faster now, and that’s kind of our short term goal, because the moment we can do that, especially going back to the whole like our customers are going to talk to our next set of customers, kind of feedback loop that we’re going through here.

If we can get the ones that have just signed today to basically get going as soon as possible, it’s going to just increase the speed of that. So that’s what we’re really focusing on the next four months, that the naturalness of our voices.

So we’ve been working on a new voice model internally. That’s pretty, pretty good, but we’re trying to get fast.

Long term, there’s, there’s a couple different plays going on here, given the tools that we it we’ve talked about is we kind of want to make those tools accessible to other AI tools and build like a marketplace, maybe around that as well, so it no one has done what we’re doing because it’s really hard and very annoying to do so, and you kind of need, like the right contacts to do in so if we can make it easier for other developers and other like companies to set up shop, that kind of just opens a whole new can of worms of just now, not only are we going to be The best chat agent for enterprises in this space to use.

We’re going to have the best voice outbound agent, the better enterprise can use. And now, when other people from other spaces or tools that they’re already using can’t hook into their system, we can be that layer that helps those tools hook into their system.

And it just it’s going to be this very cohesive system of just like allowing AIS to work with these older institutions that other development shops focused on.

So it’s finally just kind of giving them the opportunity to modernize all their tools, and hoping that once we do that, and if we can build those adapter layers, that the other providers can come in and start, you know, bring these guys into the present. 

Question:

How are you managing your work-life balance 

Answer: 

it’s gonna sound weird, but it’s gotten a lot better because we have an office now for me, I guess. But like, because we have the office now, when I leave the office, I just try not to do any more work for the most part. But yeah, it’s it’s definitely been difficult.

It’s gotten a little easier, and now that we’re growing, we’re finally hiring more people. So a lot of my time is just it’s spent differently than it used to, like I used to just be hands on keyboard constantly, just basically churning out code these days, just due to, like, the different cycle of work.

Even though I’m probably working more hours than a typical person would, because it’s different kind of work, the burnout doesn’t get to me as much as it used to.

So one that’s super helpful, just being able to kind of transition from different kinds of work and then two, like you gotta, you gotta keep your weekends, right?

You gotta have, like, a day, maybe two days, where you can just make sure you got all your stuff in order, and just at least try not to think about it, so you can come back refreshed. And that’s kind of how I, I handle it,

Question: 

What do you do outside of work, to recharge?

Answer: 

I longboard when the weather is nice. It’s just nice to put some music on and just go out for an hour or two, and then I’ve been three modeling and 3d printing, just little like, knick knacks.

A lot of my cousins are having kids now, so I just make them toys. It’s fun.

Question: 

What’s one fact about you or the company that people might not know?

Answer: 

We had a voting session about what the company’s name should be, and I submitted the name, pigeon.ai, and it won, but got vetoed, so we could have been pigeon instead of AviaryAI. So it’s named aviary because, um, we originally started this voice AI company, and going back to the whole pigeon thing, I made my case for it.

Um, I was thinking about messenger pigeons, but then when blessings started presenting it out, he just thought everyone thought it sounded like a like, apparently everyone thinks pigeons are gross. I think they’re kind of cute, but yeah. So he was just like, yeah, no one likes that, but we wanted to keep the bird thing. So it was like,

Okay, well, messenger birds go into an aviary. Or the next answer was pigeon coupe. But you can’t just have the word pigeon in it for some reason.

Yeah. So that’s how we kind of got to aviary, and it’s really funny, all of our internal services inside are named after birds. So like, look at all of our code bases. There’s just different bird names. So our our entire GitHub just looks insane.

Eric Schneider Founder and Co-CEO of AKKO

Company Overview:

Eric Schneider is Founder and Co-CEO of AKKO, a U.S. startup offering device protection plans for individuals and businesses.

Their flagship “Everything Protected” plan covers personal items against damage and theft.

For businesses, they provide customizable insurance solutions across various industries, including embedded plans for resellers. In April 2024, AKKO acquired Upsie, enhancing support for channel partners.

Their offerings are backed by an “A” Rated insurer, ensuring reliability in coverage.

Can you tell us a little about your background before starting Akko?

Before AKKO, my career spanned several worlds—engineering, consulting, investing, and startup incubation.

I started out as a jet engine engineer at General Electric through their Edison Engineering Leadership Program, before moving into management and strategy consulting at L.E.K. Consulting. While at L.E.K., I took the GMAT and realized how many students lack access to quality test prep.

That inspired me to found Grad Mentors, a nonprofit offering free GMAT and GRE mentoring to students from underserved backgrounds.

It was my first real taste of entrepreneurship, and it showed me how powerful it can be to build something from scratch that helps people. After that, I attended Harvard Business School and joined 25madison, a NYC-based venture studio.

There, I had the opportunity to work with and invest in early-stage startups—experiences that ultimately led me to co-found AKKO.

What inspired you to become a founder, and how did you identify the need for your product/service in the market?

I enjoy solving real problems and building high-performing teams to tackle them. The idea for AKKO came from my co-founder Jared’s frustrating experience trying to repair a damaged laptop. I’d had similar pain with phone insurance: confusing terms, hidden “gotchas,” and a slow, outdated claims process.

As we dug deeper, we realized consumers weren’t the only ones frustrated—resellers and partners lacked modern, reliable ways to offer protection at key points in the customer journey.

Those relying on legacy providers were stuck with inflexible products and poor user experiences that reflected badly on their brand. We saw an opportunity to fix all of that—with tech, transparency, and a better platform.

How did you start your company? What were the first steps you took to get it off the ground?

We launched by partnering with a small insurance carrier to test our product DTC and gather early data. That allowed us to iterate on coverage, UX, and claims experience.

We secured reviews from tech publishers, recruited a nationwide network of local repair shops, and prioritized high-quality in-person repair options over clunky mail-in processes.

At the same time, we interviewed industry players—particularly those underserved by existing solutions—to understand their needs. That shaped our go-to-market strategy, targeting B2B2C partners that couldn’t launch or scale protection programs with incumbent providers.

What innovations or unique features set your company apart from others in the industry?

AKKO is a fully modern platform built from the ground up to serve both end users and distribution partners. We offer:

A fully digital, mostly automated claims process that’s earned us the highest ratings in the industry.

A modular platform that’s configurable across verticals—MVNOs, OEMs, retailers, ISPs, fintechs, education, and enterprise.

A massive distributed repair network: 1,500+ vetted local shops, 1,500+ additional retail outlets (Apple, CPR, etc.), and multiple depots offering fulfillment, logistics, and bulk repair services.

Fraud prevention tools via AI-enhanced image/video verification, device tracking, and location tech.

We’re not centralized around our own repair facilities—we’re a dynamic network that routes claims efficiently to the best option per device, geography, and use case.


What has been the most effective strategy for scaling your business?

A few main strategies have driven our growth:

  1. Hiring experienced industry leaders across key verticals to lead channel-specific growth. Their deep expertise has helped us move quickly, build trust, and tailor our approach for each market.
  2. Building our consumer brand early to validate the product and optimize the customer experience. That brand foundation gave us credibility, helping partners feel confident that AKKO could be a seamless and high-quality extension of their own offerings.
  3. Prioritizing configurability and flexibility at scale—enabling us to truly align with our reseller partners’ goals. Our modular platform allows us to tailor coverage, claims flows, and integrations to meet the specific needs of each partner. We treat resellers as core customers, designing with their business objectives in mind.
  4. Leveraging a tech-forward, API-first approach to partner enablement. We’ve built flexible systems that integrate easily into existing partner stacks—whether that’s embedding protection in device checkouts, automating claims, or powering full white-labeled storefronts. This infrastructure allows us to support modern distribution at scale, while keeping the experience frictionless.

All of this is grounded in ongoing feedback from both consumers and partners, which has guided our development and led to expansion into verticals like education.

Looking ahead, what are your goals for the future of your company?

Ultimately, our goal is to continue providing immense value to our partners and their customers—while moving faster and building better than the few legacy incumbents in our space.

The electronic insurance market is large, growing, and still underserved. There’s a significant opportunity to both expand the market and take share—both of which we’re doing today.

We’re seeing strong growth across B2B(2C) channels, and increasing demand from business and education end-users, where modern, scalable protection solutions are still hard to find.

We’ve also received interest in international licensing of our platform, which we see as a powerful way to extend our reach and bring our industry-leading user experience and infrastructure to new markets around the world.

Paul Neyman, Co-Founder & CRO at Areti Health

Company Overview:

Paul Neyman, Co-Founder & CRO at Areti Health is revolutionizing clinical trial recruitment by transforming months-long timelines into just weeks.

By combining multi-channel lead engagement, AI coordination, and workflow automation, Areti connects EMR, CTMS, and CRM systems to streamline the entire recruitment process.

Their platform delivers immediate 24/7 responses, automates scheduling and follow-ups, and has already supported over 70 studies while saving 22,600+ hours in manual workflows. Areti makes recruitment infinitely scalable—with zero call teams required.



Can you tell us a little about your background before starting AretiHealth?


I graduated as a CS engineer from UC Berkeley, and was an early hire in several startups before moving into sales engineering, and ultimately into sales.

I realized I was a lot more interested in listening to customers, understanding their problems and building a solution for them, than in taking a designed spec from the product team and coding it up.

B2B sales attracted me most, and in my last two companies I was selling life-saving critical emergency messaging solution, and one of my verticals was healthcare.

I learned about the need for a trusted and engaging message that gets people’s attention and gives them clear direction on where to go and what to do.

What inspired you to become a founder, and how did you identify the need for AretiHealth in the market?

My long-time friend and Founder of Areti Health is Ilya Gluhovksy. We met when we were students (he was a graduate at Stanford, I was an undergrad at UC Berkeley).

We kept in touch through the years, and met for lunch to discuss his latest idea: using generative AI to talk to people who would be interested in clinical trials. One of the biggest hurdles in the industry is that it’s a manual task, done by CRCs (Clinical Research Coordinators) calling on potential candidates, playing phone tag, experiencing massive delays and a huge churn to get to a few qualified leads. Generative AI could dramatically boost this and automate the whole process.

Ilya had developed a prototype and received early interest, but needed a partner with sales acumen to drive the deals to closure. I had experience with selling B2B communication tools, experience in the healthcare industry and technical background to drive the deals. It was a perfect opportunity.

How did you start AretiHealth? What were the first steps you took to get it off the ground?

I ran Ilya’s idea through my rolodex of healthcare connections, and was met with positive reactions, interest, and even enthusiasm. I was able to quickly schedule a few meetings, validate that the idea indeed has legs, and then we decided to go for it.

Our first move onto the industry scene was at a sizeable conference in DC, and I did the legwork to secure as many meetings as possible throughout the three days.

We walked the floor non-stop, booth to booth, showing our product, gauging interest, answering questions and scoring leads. Our biggest breakthrough came from securing a meeting with the GM of a very large CRO who called up her entire leadership team for a demo to see our product.

It ran overtime – instead of a 20-minute pitch, we stayed in the room for 40 minutes, with the senior staff experiencing our solution for themselves.

This gave us a start and an entry into the industry. We came back from the conference armed with a stack of leads to follow through, a huge product debt and high aspirations.

Next was the typical sales grind – chasing conference leads, setting up pilots, doing pricing exercises, validating our ideas, launching first customers, going to more conferences, increasing pipeline – and in parallel, preparing for our seed round: signing as many early contracts as we could, creating pitch deck, canvassing valley VCs for the right fit, doing pitches and regrouping for a better message, targeting, impression – and so on.

What were some of the biggest challenges you faced in the early stages of building your company?

We started Areti when there was nobody else doing it, and so part of the challenge was educating the industry, which can be notoriously conservative, that use of generative AI is not only feasible, but actually a tremendous benefit to everyone: from research sites to CROs to Sponsors. Overcoming healthy skepticism and “we’ve never done it this way” was a challenge.

What innovations or unique features set your company apart from others in the industry?


We have by now amassed tens of thousands of patient profiles which allow us to better target the message, get unique insights on study feasibility, partner early on with key players in the industry who have even more data – all to increase the speed and efficiency of engagement.

We’ve learned some behavioral tricks that allow us to optimize engagement, with the goal of prescreening and qualifying as many patients into the study and as quickly as possible.


What advice would you give to other founders or entrepreneurs starting in healthcare or health tech?

This is a very close-knit industry. A bad implementation or bad experience can torpedo your entire company, because these professionals all know each other and exchange information constantly. Reputation is really everything.

It is better to focus on few early customers, but make them as successful as possible, so they can propel you towards others with their success – which is exactly what happened with us.


Looking ahead, what are your goals for the future of your company?


We want to become industry standard de-facto for recruiting. Our database of patients grows at an exponential rate, along with our insights and knowledge.

At some point, we would like for every recruitment campaign to be leveraging what we brought into the field.