The Vertical Moat: Finding the Billion-Dollar Gaps the Giants Can’t Touch

Startup

I have a habit of seeing things that aren’t there—or rather, seeing the massive gaps that everyone else is stepping over.

Over the past decade, I’ve built five companies, secured over $2M in NIH grants, and been granted 20 patents. From systems engineering to raising capital, I thrive on the “hard stuff”—the complex, regulated, messy markets like healthcare, climate, and education that scare away most founders.

I don’t say this to brag, but to offer context on how I look at the world. When I started CareBand, I didn’t just see a wearable; I identified a fundamental gap in connectivity infrastructure. I saw the potential of LPWAN (Low Power Wide Area Networks) long before it was a buzzword, patented the technology, and used it to help people living with dementia.

I’m seeing that same signal again today. But this time, it’s not in hardware protocols—it’s in data models.

We are currently witnessing a massive, overlooked opportunity in what I call Vertical vs. Horizontal Asymmetry. And it is the single biggest opportunity for founders who are willing to go deep rather than wide.

The “Everything Store” Trap

We live in the era of the Horizontal Platform. Companies like Salesforce, ZoomInfo, and Hubspot have built empires by creating tools that work for “everyone.”

To scale horizontally, these platforms make a necessary trade-off: they must standardize. To serve a bank, a SaaS startup, and a manufacturing plant all at once, they flatten the world into generic objects. In their databases, the world looks like this:

  • Company
  • Contact
  • Deal

For 80% of the economy, this works fine. But for the other 20%—the complex, regulated, hierarchical industries—this model is broken.

The Exception: The “Massive Distribution” Play

Now, I want to be clear: there is another way to win, but it is a game reserved for the giants.

Some entities play the long game of “Start Broad, Niche Later.” They build something that does everything for everyone, achieve massive distribution, and then rely on user behavior to tell them what they actually built.

The Apple Watch is the perfect example. When it launched in 2015, it was a confused product. Was it jewelry? A mini-iPhone? A notification center? Apple cast a wide net, essentially saying, “Here is a computer on your wrist—you figure out what it’s for.” It was expensive and messy. But because they had massive distribution and cash reserves, they could afford the trial and error. Eventually, the data screamed “Health,” and they pivoted hard. They niched down into healthcare after they already owned the wrist.

OpenAI is attempting the same feat right now with ChatGPT. They released a broad, general-purpose “brain” to the entire world. They achieved instant, massive distribution. Now, they are in the messy middle—trying to figure out if they should niche down into coding, enterprise search, or creative writing. Time will tell if they can successfully specialize, or if they will be eaten by vertical competitors who solve specific problems better.

But here is the reality for the rest of us: This strategy costs billions. It requires a long runway for “trial and error” that most startups simply don’t have. If you don’t have Apple’s bank account or OpenAI’s hype cycle, you cannot afford to start broad. You have to know your customer’s pain points and start deep.

The Asymmetry of Nuance

This is where the opportunity lies for the builder. There are massive verticals where the “generic” data model doesn’t just fail to add value; it actively obscures reality.

I’m currently building a side project called SignalScout, a signal intelligence platform for the US K-12 EdTech market. Why? Because when I looked at the leading B2B signal platforms, I realized they were fundamentally incapable of understanding the US education system without breaking their own architecture.

Here is the asymmetry:

  • The Generic View: A B2B platform sees “New York BOCES” as just another Account with 50 employees.
  • The Vertical Reality: In the US K-12 market, a BOCES (Board of Cooperative Educational Services) is a powerful regional node that controls purchasing for 20+ school districts.

If you treat a BOCES like a standard business account, you miss the leverage. You miss the fact that winning that one relationship unlocks access to 50,000 students across 15 districts.

This is exactly what Naval Ravikant describes as Specific Knowledge—knowledge that cannot be trained, outsourced, or easily automated. It is knowledge earned only through genuine curiosity and deep immersion in the problem.

ZoomInfo can hire a thousand engineers to scrape websites, but they cannot code for context they don’t possess. They can’t scrape the intuition that tells you a BOCES Director is 20x more valuable than a District Principal. That specific knowledge is the moat.

Generic platforms can’t simply “add a feature” to fix this. To properly map the US education market, you need a 6-level hierarchy (Federal → State → Regional → District → School → Department). If a horizontal platform tried to implement this, they would ruin their user experience for their banking and retail customers.

They cannot cross this moat without breaking their data models.

Finding the Signals in the Noise

This pattern repeats everywhere if you know where to look. It’s about finding the friction where “standard” tech meets “specialized” human behavior.

Take Healthcare, another space I’ve spent years in. If you try to build a sales intelligence tool for selling to doctors using the standard “LinkedIn Scraping” playbook, you will fail.

  • The Horizontal Assumption: “Professionals are active on LinkedIn.”
  • The Vertical Reality: Doctors are almost never on LinkedIn. They hang out on Doximity, in medical journals, and at conferences.

Generic platforms are blind to these signals because they are looking in the wrong places. They are optimizing for the tech-savvy SaaS buyer, not the Chief Medical Officer or the District Superintendent.

The Builder’s Advantage

This is why I love building now more than ever. Whether I’m running my own startups or acting as a strategic advisor for other founders, I look for these structural disconnects.

We often think “innovation” means inventing a new AI model or a new piece of hardware. Sometimes it does. But often, innovation is simply having the discipline to respect the complexity of a specific market.

With SignalScout, we aren’t trying to be the “ZoomInfo of everything.” We are choosing to be the undeniable expert in one thing: US K-12 Education. We are building the map that the giants can’t draw.

For the founders and builders out there: Unless you have the resources to be Apple, stop trying to beat the incumbents at their own game. Don’t build a better general-purpose CRM. Look for the pockets of the world that are too complex, too messy, and too hierarchical for the giants to touch.

Find the asymmetry. That’s where the value is.

The “3-Person Unicorn” Has a Fatal Flaw: It Forgot the Architect

Uncategorized

I’ve been reading a lot about building startups and founding teams in the new AI-era. I came across the NFX article on the “3-Person Unicorn Startup” after seeing a few friends on Linkedin talking about it. If you haven’t read it, the thesis is compelling. It argues that with the leverage of Generative AI, the next billion-dollar company will be built by just three people: a CEO (the seller), a CTO (the builder), and a broad Generalist (the operator).

I love the optimism of this concept. I love solving hard problems with emerging technologies, and I thrive on the idea that small, insanely smart teams can outmaneuver incumbents.

However, I believe this model overlooks a critical organ in the startup anatomy.

The NFX framework assumes that if you can code it and sell it, you have a business. But after a decade of building companies, securing patents, and navigating the unforgiving terrain of healthcare and hard tech, I see a massive gap in this 3-person lineup.

They are missing the Experience Architect.

You need a human obsessed with design interaction and holistic optimization. If you don’t have this, you might build a technical marvel that solves the world’s biggest problems, but you will end up with a “shit product” that no one can actually use.

The Illusion of AI Competence in Design

I have built 5 companies and grown 2 of them to significant annual recurring revenue. I have successfully applied for and won 10 NIH grants, resulting in over $2 million in non-dilutive funding. In my world, which often intersects with healthcare, education, data governance, and complex hardware, “user error” isn’t just a churn metric. It is a failed clinical trial or a rejected patent.

I see founders falling into a trap where they believe AI covers the “design” vertical because it can generate CSS or copycat a landing page structure.

This is a mistake.

AI models today are incredible at execution. They can write the Python script to analyze data. They can draft the SQL query. But most AI models cannot think through the experience wholistically. They cannot navigate the infinite and often illogical permutations of user actions.

AI does not have empathy. It cannot feel the frustration of a nurse trying to input patient data at 3 AM. It cannot sense the friction a non-technical user feels when navigating a climate-tech dashboard.

AI can help with bringing in design and Product-Led Growth (PLG) best practices, but you need a human in the loop to navigate and decide.

The Missing Founder

In the NFX model, the CTO is leveraging AI to code faster. The CEO is leveraging AI to sell faster. But who is ensuring the product actually makes sense?

I believe you need one of your co-founders to be purely interaction-focused.

Alternatively, if your team is truly limited to three people, the “Generalist” cannot just be an operations person. They must be a product designer who understands systems engineering.

I have seen technically superior products fail because the interaction layer was treated as an afterthought. In the age of AI, features are becoming a commodity. The code is cheap. The logic is accessible.

The moat is no longer “can we build it?” The moat is “does using this feel like magic?”

Why Systems Thinking Matters More Than Ever

My passion for building expresses itself in two ways. I run my own startups, and I serve as a commercialization partner for other innovators. I help founders navigate the path from a raw idea to a defensible product.

When I look at my work in systems engineering and cloud infrastructure, I see that complexity is increasing, not decreasing. AI adds layers of capability, but it also adds noise.

A pure coder (CTO) often thinks in terms of efficiency and inputs/outputs. A pure seller (CEO) thinks in terms of value propositions.

The Experience Person thinks in terms of flow.

I have spoken at conferences around the world from the LoRa Alliance World Expo in Paris to TEDx in Dayton, Ohio, talking about how technology shapes the world. One constant truth I have observed is that human attention is the scarcest resource.

If you rely on AI to design your product flow, you are relying on a statistical average of what already exists. You aren’t innovating on the experience. You are regressing to the mean

.

The Revised Playbook

I am not arguing against the lean startup. I have managed hardware, software, and research teams, and I know the power of keeping headcount low. But if I were building a “3-Person Unicorn” today, specifically in high-stakes markets like education, climate, or health, I would tweak the roster.

  1. The Visionary/Seller (CEO): Finds the market and tells the story.
  2. The AI-Augmented Builder (CTO): Orchestrates the code and infrastructure.
  3. The Experience Architect (CDO/CPO): The human in the loop. The person who translates “best practices” into a specific, optimized user journey.

If you leave that third seat empty, or fill it with a generic operator, you will build a fast car with square wheels.

We are entering a golden age of building. The barrier to entry has never been lower. But the bar for user experience has never been higher.

Don’t let the AI do the thinking for you. Let it do the work. You do the design.

The 90% Margin Paradox

Education Walkthrough, Lessons, Startup

Last Monday, I was on my monthly advisors call discussing design updates to our pricing page. This came right after I’d shared news about a big deal that forced me to rethink everything. The prospect didn’t want to manage individual licenses and requested per-campus pricing with unlimited users. I scrambled to create tiered pricing that decreased per campus as volume increased. I thought nothing of it—just a routine sales update.

Then I showed my advisors the pricing page.

I was expecting feedback on design, instead they spent 30 minutes dissecting our pricing model. Our PLG advisor asked a simple (but dangerous) question that made my head spin: “What if you offered unlimited licenses per school for a set price to reduce your sales cycle?”

My knee-jerk response was defensive: “We can’t do that. We’re on a single-user license model. We charge per user.” But the question haunted me all week. Why was I so attached to per-seat pricing when our margins could support almost any model?

Most SaaS founders dream of 90% gross margins. But when you achieve them, you discover something counterintuitive: they create more pricing problems than they solve.

The traditional business school approach to pricing (cost plus reasonable margin) becomes meaningless when your marginal cost approaches zero. A founder recently told me he spends more on coffee for his team each month than on server costs for all his customers. This isn’t a scaling problem; it’s a pricing philosophy crisis.

The Friction Trap

When you price per seat at $15/month, you think you’re being reasonable. After all, that’s less than a lunch. But watch what happens during a demo. The prospect gets excited about your product, then asks the fatal question: “How much for our 200-person team?”

Three thousand dollars a month suddenly doesn’t sound like lunch money. Worse, you’ve just killed your PLG motion. Nobody wants to be the person who adds $180 annually to the company budget every time they invite a colleague.

This is the paradox of per-seat pricing with high margins: it penalizes exactly the behavior you want to encourage (viral adoption within organizations).

The Figma Insight

Figma understood something profound about pricing software with negligible marginal costs. They realized that design collaboration has two types of users: creators and spectators. Spectators add zero incremental cost but drive viral adoption. So they made viewing free and charged only for editing.

This wasn’t generosity; it was strategic thinking. Every free viewer becomes a potential advocate for upgrading the team to more editor seats. The viral coefficient of their PLG motion increased dramatically because sharing had no cost friction.

The Notion Bet

Notion took this logic even further. Unlimited users for $8/month sounds insane until you understand their bet: they’re not monetizing people, they’re monetizing sophistication. A 1,000-person company can use basic Notion for $8/month total. But as they grow sophisticated—advanced permissions, integrations, analytics—they’ll upgrade to higher tiers.

This only works with extremely high margins. Notion can afford to have enterprise teams using their product essentially for free because they’re betting on feature expansion over time. Their unit economics make this sustainable in ways that would bankrupt a 20% margin business.

The Bootstrap Advantage

Interestingly, bootstrap founders often have more pricing flexibility than their venture-backed counterparts. Without investors demanding specific growth metrics, they can optimize for long-term sustainability over quarterly ARR targets.

When venture-backed competitors launch aggressive freemium models subsidized by investor capital, bootstrap founders with high margins can play a different game entirely. They can focus on building sustainable unit economics while competitors burn cash trying to buy market share.

The Enterprise Paradox

Here’s what nobody tells you about high-margin SaaS pricing: sometimes your biggest customers should pay the least per user. A 10-person team getting $50,000/year of value might happily pay $500/month. But a 500-person team getting $500,000/year of value will balk at $25,000/month, even though their per-user value is identical.

This violates our sense of fairness, but it reflects economic reality. Large organizations have different budget processes, approval chains, and price sensitivity. Your pricing model needs to account for these organizational dynamics, not just mathematical proportionality.

Finding Your Model

The right pricing strategy for high-margin SaaS depends on understanding your viral mechanics. Ask yourself:

Does value correlate with team size, or with usage intensity? Slack chose per-user because communication value increases with network size. But Superhuman chose flat-rate because email efficiency is personal, not collaborative.

What drives expansion within accounts? If it’s adding users, per-seat makes sense. If it’s feature sophistication, tier-based pricing works better. If it’s outcome achievement, consider usage-based or outcome-based models.

Where does friction kill adoption? Every pricing boundary creates adoption friction. The question is whether that friction prevents valuable usage or just prevents unprofitable usage.

The Uncomfortable Truth

The hardest part of pricing high-margin software isn’t finding the right price. It’s overcoming the psychological discomfort of charging far less than the value you create. When a founder realizes their $50/month tool saves customers $5,000/month, their instinct is to raise prices 10x. Sometimes that’s right, but often it misses the bigger opportunity.

The goal isn’t to capture maximum value from each customer today. It’s to remove every barrier to your product spreading through the market like a virus. With 90% margins, you can afford to optimize for ubiquity over unit economics, at least until you achieve market dominance.

The companies that understand this paradox (that high margins enable lower prices, not higher ones) often end up building the most valuable businesses. They sacrifice short-term revenue optimization for long-term market capture, betting that ubiquity beats margin optimization when your costs are near zero.

This is perhaps the most counterintuitive lesson of high-margin SaaS: your pricing strategy should be as much about what you don’t charge for as what you do.

Between Dazzle and Delivery: Should Startups Chase the CES Spotlight or Build in the Shadows?

Startup

Every January, countless tech enthusiasts descend upon CES (the Consumer Electronics Show) to feast their eyes on what’s next. Big corporations roll out dazzling prototypes—holographic displays, AI-driven wearables, self-driving contraptions—all flanked by dramatic music and slick presentations. It’s the closest thing the tech world has to a circus under neon lights: impressive, enthralling, and—more often than not—gone with barely a trace once the spotlight shifts. Why? Because for many of these giants, the real goal is to generate headlines, reassure shareholders, and overshadow competitors. If the prototype never becomes a mass-market product, well, it’s just another footnote in the annals of CES hype.

But let’s talk about the folks who don’t have the luxury of spinning ephemeral visions: startups. Should they replicate the same “look-at-me” theatrics? After all, drawing attention early could be the difference between securing a round of funding or fading into oblivion. On the other hand, hype without substance can quickly become a death knell for a nascent venture. While a multinational can laugh off a failed prototype as a mere R&D experiment, a startup might blow half its runway perfecting a smoke-and-mirrors demonstration—only to discover that the market never asked for the thing it’s built.

Then again, there’s that undeniable allure of standing in front of a massive CES crowd or snagging headlines in January. Maybe you have a promising concept, but you’re not 100 percent there yet—should you “fake it till you make it?” Some would say yes, especially in industries that move at breakneck speed. A big reveal could attract partnerships, spark pilot programs, or drum up the investor interest you’ve been courting. Sometimes, faking it responsibly can be just enough to catapult you into “we made it” territory.

On the flip side, plenty of founders swear by stealth mode: quietly iterating, validating, and perfecting behind the scenes. They prefer smaller-scale tests with real users before they even think about unleashing a bombastic demo on the world. It might be less glamorous than a big booth at CES, but it keeps them focused on core problems and less prone to building for applause rather than need.

Ultimately, there’s no universal recipe. Some startups thrive on an audacious debut—especially if they truly have something innovative to show the world, even if it’s 80 percent complete. Others succeed by shunning spectacle until they’re certain they can deliver. One thing is for sure: the marketplace is littered with head-turning prototypes that never saw the light of day. If you’re prepared to blow your trumpet, just be ready for the inevitable question: “When can we buy it?” If your answer is less certain than your onstage swagger, that’s where trouble begins. Then again, if hype is the rocket fuel you need to reach orbit, go for it—just remember that after takeoff, you’ll actually have to fly.

Read more about my experience: CES 2018 Review – A Startup in a Land of Corporations 

Zone of Genius

Education Walkthrough, Startup

I have figured out a lot of the pieces in Education Walkthrough’s operations, yet I am still working on sales. With our emphasis on PLG and organic growth, finding the right fit of a person or an advisor to support us has been more challenging.

This week, I had multiple calls from various sales gurus, coaches, and consultants to try to figure out a solution. All of them blurred together except one. This guy talked about systems and processes, starting by looking at the business holistically and then matching you up with experienced operators (former entrepreneurs) to coach you. He was talking my language.

Halfway through the conversation, he said, “If we do our job right, then the result will be cutting down the time you are doing on sales and giving you more time in your zone of genius.”

My zone of genius. Interesting.

It stuck with me. I had heard the term before, but it had only been a while. I have been thinking about the concept since the call.

Where is my zone of genius? Where do I love to be? 

For me, my passion is in product. It is abundantly clear to the people around me. I love to take a lot of information in from people, the internet, customers, videos, and what you have, then sit on it and synthesize it into insights, pattern matching, or actions. That is what I am good at and where my zone is.

I have learned that things don’t happen immediately in life, so I have learned to let things simmer in my zone, where I can do this process for a long time, then at each juncture when I have an insight, write it down immediately. I need to capture it so I can turn back to it and reflect or use it as a jumping-off point for the future. 

This has become my superpower. My zone of genius. 

If I really did not have to worry about sales or marketing and could just focus on this, would I be happy?

There is value in optimizing for your zone of genius while also spending time outside of your zone. Remaining uncomfortable is one of the greatest tricks of successful people. There is probably a balance here between being inside your zone and outside.

It’s funny what things stick with you from a random call on a Tuesday across all the other things you did during the week.

Startups Stop Chasing Deer in the Forest. There’s a Better Way

Lessons, Startup

I’ve been trying to explain the difference between push and pull marketing to early stage founders—and investors – for years. And finally, on a recent mentoring call, it clicked. The perfect analogy just dropped into my head:

Hunters don’t run screaming through the forest hoping to magically crash into a deer.

Why do so many startups (and brands) act like this?

Push Marketing: The Forest Sprint

Most early-stage founders default to what I’d call the “push” approach:

  • Cold emailing hundreds or thousands of people
  • Cold DMs
  • Cold calls
  • Cold everything

It’s frantic, exhausting, and wildly inefficient—like sprinting through a forest hoping to stumble into a deer. Sure, you might bump into one eventually. But is that really the best use of your energy?

I’m Guilty Too

Let me be real for a second: I’ve done this. I’ve pushed.

Sometimes it feels easier to just do something, even if it’s not the right thing. Pushing feels productive in the moment—but it’s usually just noise. Most of the time, it burns time and energy without meaningful results.

I’ve had to catch myself, take a step back, and consciously switch back to a pull mindset.

It’s not always easy. But it’s worth it.

Pull Marketing: Set the Trap, Then Wait

Great hunters don’t chase deer. They understand the terrain, know where the deer go, and set up shop. They wait. Watch. Then they take the shot when the moment is right.

That’s pull marketing.

In startup terms:

  • Hosting a podcast or blog that draws in your exact audience
  • Building a community or newsletter
  • Speaking at the right conferences (aka, where the deer are)
  • Creating useful content that attracts your ideal customers
  • Making yourself findable for the people already looking

You attract, then you act.

What Most Founders Get Wrong

I’ve seen this mistake over and over: founders spend all their time “pushing” instead of building something that pulls people in.

They forget the world has flipped. People don’t want to be chased. They want to discover something interesting. Something useful. Something aligned with their needs.

In the forest of startups, you don’t need to run. You need to learn the land, set up shop, and wait for the right deer to wander in.

You won’t catch every one. Some shots will miss. But your odds? Way better.

Outsmarting the Job Hunt

Lessons, Systems

Recently, friends and family have been asking me for job-hunting advice. Of course, I am happy to help, but I do find the request a little odd because they know that I haven’t held, let alone applied for, a traditional job since my consulting days post-college. Maybe they are looking for some inspiration that is different than the typical job-hunting advice, not sure, but I do know that my entrepreneurial experience has given me insights into hiring.

The Most Creative Approach

One memorable method was from a guy who wanted to work at CareBand. Instead of applying directly, he researched and wrote a strategic article (read the article here) about the company, offering recommendations as if he were the CEO. He sent this to me and other CEOs who he wrote about via LinkedIn or email.

I was thoroughly impressed and frankly caught off guard by this approach. It showed dedication, interest, and hard work. Although he wasn’t the right fit for us, he eventually landed a job he loved using this method.

The Most Strategic Approach

Getting a job is just a funnel, and as I have shared before the fundamentals of funnels are everywhere. A funnel is a step-by-step process with well-defined steps, conversions, and outcomes. With this strategy, getting a job is a numbers game. Here’s how to approach it:

  1. Target List: Identify companies that interest you, regardless of if they have active job postings.
  2. Network List: List your LinkedIn contacts working in interesting jobs.
  3. Connection Mapping: Note connections or introductions needed to reach a person at each company.
  4. Cheat Sheet: Prepare templates for LinkedIn and email connections (catch up, cold connect, introduction request). You will use these to copy, paste, and tweak when connecting with people
  5. Self-Assessment: Answer key questions about your skills, past experiences, and job preferences.
    • What did I learn at my last company?
    • Why am I looking for a new job?
    • What skills do I have?
    • What am I uniquely qualified to do? Where am I a subject matter expert (SME)?
    • What do I want to do?
    • What do I not want to do?

Lastly, create a google sheet to track your progress. Start connecting with people and asking for 30 minutes of their time to catch up and pick their brain about their careers, then at the end of the conversation see if they or someone they has a spot open for you. Track the way you met, date of meeting, and follow up on the sheet so you can see your progress. The goal is to have as many conversations as possible to learn about opportunities and get referrals.

Tips:

  • Be clear with your answers.
  • Create a free calendar link for easy meeting scheduling (i.e. calendly)
  • Be direct and set clear expectations.
  • Get comfortable with asking for help.

This is the most strategic and most effective way to get a job (in my opinion). I always say that you are going to get a job through talking to people, not applying with the masses. Sometimes (if you are really a catch), companies/ people will create a job for you and you will get to write your own job description.

The Least Effective Way

Applying through job websites is the most common but least effective method. I’d say 90% of people go through this process. It’s slow, competitive, and leaves you with little control. You’re just another applicant in the crowd.

It is hard to get a job today. Its a crowded and virtual market. Anything you can do to stand out and be unique goes a long way. Good luck.

Founder’s Therapy Prizes

Uncategorized
BookMy Reasons
The Referral of a LifetimeI loved this book because it underscores the importance of nurturing solid and lasting relationships to generate a continuous flow of referrals for my business. The practical strategies and systematic approach Tim Templeton outlines helped me transform even casual acquaintances and satisfied customers into lifelong sources of referrals. I believe in the power of personal connections and appreciate how this approach provides a sustainable, cost-effective marketing strategy that supports my startup’s growth.
The $100 StartupI was drawn to this book because it celebrates the entrepreneurial spirit and focuses on launching businesses with minimal capital. Chris Guillebeau’s collection of case studies and insights from people who turned their passions into profits resonated with me. I love the emphasis on lean startup principles and found inspiration and practical guidance for starting my own business on a tight budget.
The Infinite GameMy approach to entrepreneurship deeply influenced Simon Sinek’s concept of treating business as an infinite game, where the goal is longevity and continuous innovation rather than short-term wins. I believe in building a business with a long-term vision and appreciate the importance of staying adaptable and resilient.
Holstee Gift CardHolstee is more than just a brand; it’s a community that champions mindful living and sustainability. I admire how they’ve turned the principles of the Holstee Manifesto into a tangible ethos for their products and collaborations. Their commitment to ethical practices and eco-friendly materials aligns with my belief in responsible entrepreneurship.
Coffee Catch upCoffee on me. We can talk about anything startup.

I Love Grey Companies

EW - Learning Velocity Log, Startup

Introduction

Not all innovation in the tech world comes with flashy headlines or trendy apps. Some of the most revolutionary advancements are found in “grey” companies—those operating in unglamorous but essential sectors. These companies develop software that powers businesses and generates significant revenue, often flying under the radar.

There will always be an opportunity in the grey. Now more than ever that opportunity I see is taking these “boring” companies and helping them become digital and more efficient using AI, focusing on customized ERP and CRM systems, data integrations, system migrations, and the digitalization of physical workflows or assets.

The Value of Boring Companies

“Boring” software businesses are surprisingly lucrative. These companies often produce SaaS products tailored to niche industries with high pain points. Despite their lack of mainstream appeal, they excel because they solve specific customer problems, resulting in high retention rates and profitability. Moreover, these companies typically know exactly who their customers are, reducing the need for expensive marketing campaigns and thus maintaining high margins.

Success Through Industry-Specific Solutions

Success in this realm requires a deep understanding of industry-specific problems. Combining technical expertise with domain knowledge creates a powerful synergy, enabling the development of practical solutions that meet the unique needs of these niche markets. For instance, customized ERP and CRM systems can streamline operations for dental, law, and insurance firms. These industries benefit greatly from modernized workflows and data management systems that improve efficiency and security.

Case Study: Law Firms and Modernization

Consider law firms, which often struggle with outdated systems and manual processes. Implementing customized ERP and CRM systems can transform their operations, providing seamless data integration and high security—critical for handling sensitive information. By partnering with thought leaders in the legal field, companies can gain valuable insights and credibility, making it easier to introduce innovative solutions.

The Role of AI in Boring Companies

AI can play a pivotal role in enhancing efficiency for these grey companies. For example:

  • Customized ERP and CRM Systems: AI can automate routine tasks, improve data accuracy, and provide predictive analytics to enhance decision-making.
  • Data Integrations and System Migrations: AI-powered tools can streamline the migration process, ensuring minimal downtime and data loss.
  • Digitalization of Physical Workflows or Assets: AI can convert paper-based processes into digital workflows, improving speed and accessibility while reducing errors.

The Path to Success

To succeed in this space, entrepreneurs need domain expertise that resonates with users of these niche products. This expertise can be leveraged to gain market validation and attract the first few customers. Building partnerships with industry thought leaders can also be beneficial, providing both credibility and deeper insights into customer needs.

Conclusion

Starting with the problem rather than the solution can lead to significant innovations in boring but profitable niches. There’s immense potential in flying under the VC radar, focusing on niche markets that require specialized solutions. Combining technical prowess and industry-specific knowledge is key to unlocking opportunities in these grey companies. By harnessing the power of AI, we can help these businesses become more efficient, secure, and profitable, ensuring they continue to thrive in their respective fields.