The Technology Map
What the software knows, decides, and does on its own.
The two maps every company runs on — the technology map and the people map — were both redrawn while you were running the one you have. We rebuild them together, at the pace AI actually moves.
The first is a technology map: the software, data, and systems that run the business. The second is a people map: the humans who sit around that software and make it move.
Both were drawn in a world where humans did the work that AI can now do. Both are still in place. And when a technology stops being what it was, the shape of the company built to run it stops being right too.
The companies we work with have the advantage of not having to guess what's coming. They can see, from their own numbers, that growth now costs more people than it should. That every new hire's job description reads like a workaround for software that should already know. That the shape of the org chart is a record of decisions made when the maps looked different.
You cannot get to the company you would build today by adding to the one you have. It has to be rebuilt — around better software and around fewer, better humans.
Fixing one without the other is why every AI transformation you've watched has underdelivered. New software on the old org chart just makes the old org chart faster at the wrong things. A new org chart on the old software just makes fewer people do the same broken work.
What the software knows, decides, and does on its own.
What the humans in your company are actually paid to decide.
Most executives we meet already know one of the maps is wrong. Very few have noticed that the other one is wrong for the same reason.
Size doesn't decide whether this works — posture does. The companies that get the most from us tend to recognize themselves in one of these three descriptions, whether they are a five-person startup or a five-thousand-person enterprise.
You didn't build the company you're running. You inherited it — from a founder, from a private-equity thesis, from a decade of well-intentioned growth. It works. It also feels like it costs too much to work.
You're several times bigger than when you started, and the math on adding more people to keep the same growth going has stopped making sense to you. You suspect the next chapter isn't the same company, just larger.
You have a board, an investor group, or a founding team that keeps asking about "AI strategy" and you keep answering with a slide none of you finds convincing. What you actually want is a real answer, from people who have built the systems, not the decks.
Every engagement begins with the Blueprint. It is how we — and your leadership team — arrive at a shared understanding of what is possible before anyone commits to a rebuild. From there, most companies continue into The Rebuild or a Residency; some don't, and that's a fair outcome too.
A 30-day, executive-led diagnostic. A leadership team cannot have a strategy for AI without a shared understanding of what is possible — the Blueprint builds that understanding first, then maps your current technology and current org against the company you would build today. You leave with an aligned executive team, two maps, a rebuild sequence, and a defensible number on what it costs and what it returns.
A senior team from Near Zero rewrites the core software and redesigns the team that runs it. The rebuild is in your production environment, run by your name at the top of the change log. Alongside the software, we train your existing team to work with AI, not fear it — so the people you already have become the operators of the new stack. We leave when they can run it without us.
A senior engineer and an org architect embedded inside your executive team. They keep the two maps evolving in real time — refactoring the stack, reshaping the org, and coaching your leaders and their teams to own the redesign after we leave.
Redrawing both maps at once takes a rare kind of professional — someone who can rewrite production software and, in the next meeting, redesign the org chart it runs on, in front of a board.
Every engagement is staffed by senior operators who could be principal engineers, founding CTOs, or COOs anywhere they wanted to be. Most of them already have been. No juniors. No offshore pods. No learning on your budget.
We are not selling AI. We are selling the company you would build if you were starting today, knowing what's coming. It happens to require AI. It requires a different org chart just as much.
Composite outcomes from the last few engagements. Industries and specifics are held back at our clients' request. The pattern is not.
Supervised agents resolve most inbound at first touch. The senior humans on the team spend their day on the edge cases only they can solve.
Sourcing, enrichment, and outbound run continuously in the background. Account executives spend their time in conversations, not in a CRM.
Variance, runway, and cohort analysis produced on demand by an agent chain reading directly from the ledger. The CFO reviews, doesn't assemble.
A persistent recruiting agent sources, ranks, screens, and schedules. Your people show up for the conversations that decide the hire.
Production, distribution, and analytics run end-to-end. A creative director sets the direction; the system executes across every channel.
Middle-layer decision support the operators actually trust. Data reaches the people who use it in the form they need, when they need it.
Every application is screened immediately. If your company is a fit, a booking link for a conversation with a founding partner lands in your inbox within five minutes. If it isn't, you'll still hear back — with a short note on why.