Founder Keith McCall on building companies, software, and real-world execution.
It was 1994. I was deep in the mechanics of the early web—HTTP servers, CGI, figuring out how to move real data into something a browser could render. At IBM, we were working with IBM WebExplorer, building interfaces before the world even agreed on what a “web app” was.
Every founder hears it, especially from inexperienced angel investors, or from angels who are patent lawyers (they want your business). “You should patent that.” Most don’t understand the mechanics—or the strategy. The strategy counts.
It’s exciting. Fast. Meaningful. You’re building something from nothing. But the moment someone actually considers leaving a stable role at a large company, the thinking shifts—fast.
A day ago, I said Gaussian splats were overrated. This morning, in our weekly review, our CTO pushed back. “They don’t give you the precise metrics you need… but they’re incredibly powerful for generating digital twins.” That’s the difference between opinion and execution.
"A Gaussian splat on the other hand is not raw data. It has nothing to do with LiDAR points. Each point in a Gaussian splat is a tiny coloured ellipsoid with varying size, varying rotation, and varying opacity. It isn't even captured through hardware. You can't collect Gaussian splats directly in the field." - Dr. Pragra Vaishanav
And you hear this: “What do we actually do with all this data?” That’s the blind spot. The lack of a defined outcome.
Someone new connects with me on LinkedIn every single day. And I usually accept. Why? Because I’m building a community—people who want to see what my portfolio companies are doing, learn from it, maybe even contribute to it.
This week, a question forced a reset: “What wouldn’t you do?” Not what I should do next. What I would stop doing entirely.
I’ve been doing this for over 30 years. There are a lot of stories, a lot of mistakes, a lot of things that actually worked… and most of it just sits in my head. That doesn’t feel right. So I started trying to write a little more. Not because I love writing—I don’t—but because I feel like I should be giving something back at this point.
Details in the comments.
So when he suggested applying Gaussian splats to my AgTech company, Pollen Systems, it wasn’t theoretical—it was grounded in real use: Analyze farms to optimize water, fertilizer, pesticides, and biostimulants through a continuous, living view of the field. That stuck.
I remember driving from Washington into California with my younger son—wildfires burning along the way. We were visiting schools. He was figuring out his path. I was doing what I always do—building the playlist before we went, and adding to it as we went. We ended up at University of California, Santa Cruz.
And along the way, I’ve learned something that doesn’t get talked about enough: Reputation isn’t built when things are going well. It’s built when things get uncomfortable.
I started developing software on a computer: the Sinclair ZX81, with one kilobyte of RAM. Today, you can carry 20 terabytes on a device the size of your finger. That’s not linear progress. That’s a complete reset in how we think about scale. And we’re seeing the same shift in geospatial.
We took drone captures of Elephant Mountain and pushed them through Omniris Vault—end-to-end. No external tooling. No stitched-together workflows. No handoffs. Just ingestion → processing → 3D output.
“What is this Omniris thing—and can I actually see it?” We're done explaining. The Vault is open. SO GO USE IT.
We’ve made it easy to collect and ingest drone data. But once the data lands… that’s where most systems break. Not because of the drones. Not because of the data quality. Because the pipeline wasn’t built for what happens next.
There’s a gap in how most drone operations are planned today. Pilots bounce between apps—weather, wind, GNSS—and then try to stitch it together mentally. That fragmentation wastes time and introduces risk.
Built for real industries: construction, telecom, energy, agriculture, solar, property, real estate. Check. Not demos—operations. Now we’re looking for partners to build the insight layer—the modules that turn data into decisions—just like we’ve done with Pollen Systems in agriculture. If you’re building where data meets operations, let’s talk.
One of the most interesting policies I’ve seen comes from Esri. They cap gifts at around $25. Anything beyond that gets refused. At first glance, it feels rigid. In practice, it’s clean.
At first glance, “OG” sounds like it means old guy. That’s not it. OG = “Original Gangster.” The term came out of West Coast hip-hop—most notably Ice-T’s O.G. Original Gangster. It wasn’t about age. It was about credibility earned the hard way.
I was working at IBM, making about $40,000 CAD annually — roughly $30,000 USD — living in Toronto and trying to do all the “right” things. My wife worked as a private school teacher. We bought a house, partly because that’s what you’re supposed to do, and mostly at the encouragement of our parents. In hindsight, we probably shouldn’t have.
Back in the late ’90s at Lotus Development Corporation, there was a great little tradition—when an executive walked across the stage, their theme song played. Not walk-up music… identity music. I remember watching that and thinking: what would mine be?
Almost every day, I get the same two messages: “We can help you outsource your development.” “Would you consider an offshore team to scale faster?” My response is always the same: We don’t outsource. Period.
I was on a call this morning with a group flying in from across the world—family offices, VCs, investors: early May. I gave them two options: Seattle or Woodinville. It wasn’t even close. They chose Woodinville instantly.
It was 1991. I had just graduated from the co-op program at the University of British Columbia and was stepping into my first real job at IBM. Over the previous few years, I’d worked with IBM in Vancouver and Calgary. I thought I had a plan: Build a career in sales and marketing. Keep coding as a passion on the side.
The belief model matters more than most founders think. I started my first company before I even left Microsoft. Enough time has passed that I can probably admit that without getting in trouble. In 2003, about a year before I left the Microsoft Exchange team, I intentionally took responsibility for relationships with venture capitalists. That gave me a window into a world most entrepreneurs only see from the outside. In the lead-up to Microsoft’s acquisition of Groove, I spent time with people from Sequoia, Benchmark, Accel, and others across the Valley trying to align their portfolio companies with Microsoft. I did the job. But that wasn’t the real purpose.
During COVID, getting to Chile wasn’t a trip. It was a commitment. My wife and I flew into Santiago, got tested, and waited 24 hours in a hotel. If positive? Five days in quarantine. We got lucky.
Building the 1996 Atlanta Olympic Ticket Server wasn’t the important part. The pattern behind it was.
In 1995, the web didn’t query anything. It was designed to host documents. Pages didn’t respond. They didn’t generate. They didn’t connect to live data. If you wanted a new page, you wrote a new file. Inside IBM Toronto, I built something that broke that model.
Mining: Drones are quietly rewriting how we discover minerals. Not with one sensor—but with layered intelligence.
There’s a moment, usually in the summer, when the air settles just right in Woodinville. A glass in hand, music floating across the lawn at Chateau Ste Michelle—just a half mile from our offices—and a Pacific Northwest band like Pink Martini takes the stage.
Last night at Eastside Entrepreneurs, ~30 founders gathered over 10 bottles of wine in our (relatively new) office and event space at Red Hook Brewery. The room was electric. Not because of the wine. Because of what was shared.
Crossing the Chasm: Geospatial Intelligence Has Left the Old Market Behind We are crossing a threshold at Omniris. Not iterating. Not improving. Breaking away.
What we inherited was not a polished system or platform. It was a company in disarray. We’ve had to work through delayed pilot payments, outstanding obligations, cost structure problems, and the painful realities of integrating a distressed operation. None of that was easy. Some of it was brutal.
There are places that exist for meetings. And then there are places where things actually happen. For me, the Columbia Tower Club was the latter.
Three months ago, we brought on Craig Eisler as CTO. Since then, the pace of execution has fundamentally changed. We’ve moved beyond concept into a fully operational geospatial platform.
Game on. Seven to ten years ago, ag tech ran this exact experiment. And still—no breakout outcome.
Most founders think incorporation is the milestone. It’s not. It’s the starting line.
A perspective on capturing moments, experiences, and life context in ways that persist beyond memory.
A fun throwback post blending baking, nostalgia, and a Zork-style narrative take on the classic UBC cinnamon bun recipe.
Lessons from early web infrastructure, proxies, and systems thinking that still apply to building companies today.
AI agents are only as effective as the structure of the data they operate on. Architecture determines usefulness.
Structured geospatial pipelines reveal inefficiencies, artifacts, and hidden value across drone and agricultural data systems.
A practical perspective on leadership, accountability, and building companies with clarity under pressure.
In 1994, I was a young software developer at IBM Toronto working on the Distributed Computing Environment (DCE), porting the security component Kerberos from Unix to MVS and OS/400: the operating systems behind the most serious mainframe and midrange platforms of the time. Also serious: how bad the cafeteria food was.
Founders win by turning urgency into disciplined execution rather than mistaking noise for progress.
Leadership is tested through execution, alignment, and how quickly a team can move together.
A grounded view on venture capital, timing, and what fundraising does and does not solve inside a startup.
Building in hospitality requires patience, local understanding, and execution grounded in customer experience.
Publishing, structure, and usability define whether geospatial systems actually create value.
Execution is where intent either compounds into value or disappears into delay.
Resilience is one of the most important operating assets when outcomes resist expectation.
AI and geospatial systems are converging into real-world operational platforms.
Structured, governed geospatial storage is the foundation for scalable intelligence.