Bespoke Software for Your Business / AI-Era Pricing
Senior engineering with agentic leverage. The custom software your business actually needs.
We scope the work for a fixed fee, build it for a fixed fee, and hand you the code when it’s done. Most of our clients are owner-operators stuck with a process off-the-shelf software can’t fix, or founders who need senior engineering help without giving up equity. AI tooling is part of how we work, and part of why our prices are what they are.
Why custom, why now
AI changed the build-vs-buy math.
Senior engineers working with modern AI tooling get done in weeks what used to take a quarter. That changes what’s worth building.
A system built around your operation now costs a fraction of what the big platforms charge, and it does what your process needs instead of what a vendor’s roadmap allows. We pass the speed along as fixed fees and short timelines rather than padding the margin.
A small, flexible senior team with good tooling moves quickly. You’ll see working releases early and often.
Our fixed fees that usually land well under what the big platforms charge year after year.
No per-seat pricing and no subscription. When we hand it off, it’s yours.
How we ship
A small agentic factory, run by a senior engineer.
Most shops bill you for the time a team takes to build the thing. We use our proprietary agentic software factory under the hood, with senior engineers running the factory and approving everything before it ships. Now a single principal can move at a pace that a team just can’t match, without the team’s overhead. The reason that matters to you is the fixed fee on our services menu.
It’s the same idea we apply to client work: senior judgment in the loop, with the rote work done at machine speed.
Claude CLI. MCP. SQLite context. Python orchestration. Deterministic validation. Human approval before anything ships.
Sometimes the right build is no build
Judgment first. Build second.
A platform team once asked us to roll out an enterprise data-quality tool we’d evaluated and found wasn’t a fit for their environment. Instead of installing it and writing it up, we put together a lightweight, forward-compatible framework that did the job in 200 lines of config, then handed it back to the platform team to own long-term.
That’s the part of the work we’re actually being paid for. The build is what comes after the judgment, not before it.
Who we work with
Most of our work comes from two places.
The process that runs on a spreadsheet nobody trusts.
Maybe it’s commissions in a giant Excel file, or scheduling on a whiteboard, or a CRM everyone works around instead of in. Hopefully it's not Steve-who-can-never-leave because he's the only one who can do it. You’ve looked at the big platforms and none of them quite fit. We build the version that does fit. The math tends to work out well for companies your size: big enough to need real engineering, small enough that a good system quickly pays for itself.
For operatorsSenior help for your product, without giving up equity.
The model is the glamorous half of your wedge. The half your enterprise buyer evaluates on is auth, audit logs, SSO, evals you can show procurement, the security questionnaire that closes the deal. That’s what we build. You pay cash and keep your cap table intact. You don't need FTEs right now, you just need work done. If equity makes sense for you, we’re open to the conversation, but we won’t push it.
For foundersWhat an engagement looks like
How it works, start to finish.
Discovery
We sit down with the people who live with the problem, write up the scope, and put a price on the build. If you stop there, you’ve got a plan you can hand to anyone.
Build
We build what discovery scoped, at the price discovery set. You see progress in a working demo most weeks. We like to ship early and often.
Handoff
The code goes in your repo with documentation and a runbook your team can actually use. Nothing about the engagement is built to keep you dependent on us.
Embedded operator
Some clients want us to keep running what we built, or to be the senior engineer on the agentic system they depend on. Others take it in-house on day one. Either works.
Services
A short menu, priced.
Who’s behind this
Jeremy Nay leads the work. The “& Co.” is real.
Jeremy spent twenty-some years leading engineering at several start-ups and places like Microsoft, SDL, and Expedia Group before opening the shop. Director-level seat over 39 engineers and four platforms on an $11.4M annual investment, and two U.S. patents on the Microsoft Policy Processor that shipped in Windows Server, Configuration Manager, and Intune. He runs the shop, with the agentic factory doing the rote work and his judgment doing the rest. For the larger projects, Jeremy can mobilize a team of vetted, AI-forward senior engineers to scale up.
McNee & Co. is the customer-facing name for Nay Systems LLC. There’s a short story behind the name.
Recent receipts
A career’s worth of work, in numbers.
Analyst capacity returned to a 300-person product organization, via a RAG and LLM-SQL onboarding system with deterministic validation and human-in-the-loop merge.
U.S. patents on the Microsoft Policy Processor (8,112,379 and 8,954,370). Shipped in Windows Server, Configuration Manager, and Intune.
Annual engineering investment owned across 39 engineers and four platforms at a public travel company.
Drop in credit-card fraud losses after re-architecting a monolithic detection service into a real-time microservices platform.
SIEM scale. 40% reduction in IAM operations overhead. 85% reduction in signal-onboarding effort. Different platforms, same principle: leverage instead of headcount.
Software factory in production since February 2026. One senior engineer ships at team-scale timelines, with the SDLC discipline still in place.
Client names are mostly under NDA. Happy to talk specifics on a call.
Selected work
Recent work.
A full-stack ops platform for an owner-operator.
Inventory, scheduling, and admin workflows in one practical system the owner actually uses. Replaced four disconnected tools.
Read the case study → AI-native consumer productA multi-agent career coaching platform.
Sourcing, application, and coaching agents working together as one product for role discovery, resume targeting, and job-seeker guidance. Multi-agent system in production.
Read the case study →