First
Unify
One identity. One source of truth.
We connect the systems you already run (CRM, accounting, documents, comms, identity) into a single coherent layer. Every record reconciled, every user one login.
How we work
Build the system.Then let AI earn its place.
The same three stages run under every engagement, always in this order. We use cutting-edge AI to build it all, and we’re deliberate about where AI runs once it’s live.
Who we are
There’s a lot of noise about “AI agents that run your business.” We’ve watched those projects stall, pilot after pilot. The models were rarely the problem. The system underneath was never built.
So we build the system first, with cutting-edge AI, then put AI to work inside it only where judgment is required.
Build the system right and the AI compounds it. Skip it and the AI just makes the mess move faster. That sequence is the whole company.
Why AI projects stall
If an AI project stalled, it probably wasn’t the model.
It was the system underneath it. Three failure modes show up again and again.
AI bolted onto broken process
An agent stapled on top of five disconnected tools inherits every inconsistency underneath it. The model is fine; the foundation is broken. No prompt fixes a data problem.
No single source of truth
When the CRM, the spreadsheet, and the inbox each tell a different story, "intelligent" automation just makes wrong decisions faster. Truth has to be engineered before it can be automated.
Nothing is auditable
A pure-AI workflow can rarely explain what it did, or why. The first time an output is wrong and nobody can trace it, trust evaporates and the pilot quietly dies.
The research points the same way. In McKinsey’s 2026 survey, nearly three-quarters of the companies seeing real financial results from AI had redesigned their workflows around it, against one-quarter of everyone else. Sources in our research note
Why we build in this order.
Skip the first two stages and the AI inherits every problem underneath it. This is the order that gets you to production, and keeps you there.
Then
Automate
Deterministic workflows. Zero re-keying.
With a solid substrate, the handoffs disappear. Approvals route themselves, documents file themselves, statuses update everywhere at once, and the same input produces the same result every time.
Only then
Apply structured AI
AI where judgment is needed, checked on both sides.
Only now does AI enter, and only for the judgment calls: reading documents, drafting responses, classifying exceptions. It works inside checks on both sides, and anything it is unsure of goes to a person.
The checks underneath
Four properties every system keeps.
Deterministic before intelligent
If a rule can decide it, a rule does. AI is reserved for genuine judgment calls.
Validated on both sides
Every AI step receives checked input and emits schema-validated output. Bad data is flagged before it can flow downstream.
Humans approve what matters
High-stakes actions wait for a person. The system prepares the decision; you make it.
Auditable by default
Every change timestamped and attributed, human or machine. "What happened?" is a quick query.
Working together
What an engagement looks like.
Ownership is in writing before we start, and your data is always yours.
Step 1
Consultation
45 to 60 minutes
We dig into the systems you currently run, the manual handoffs that hurt, and where you want to be in 6 to 12 months. You leave with a candid take on whether we are the right fit, and we will say so if we are not.
Step 2
Systems map & proposal
About a week
We document what you run today, where the truth lives (and where it leaks), and propose a scoped first build with a fixed deliverable. Scope, timeline, and cost in writing before any commitment.
Step 3
First build
Scoped small on purpose
A focused, production-grade slice of real software, with weekly demos. Ownership is set out in writing before the build starts, and your data is always yours.
Step 4
Operate & extend
Ongoing, month to month
Once the substrate is solid, each new automation gets cheaper to add. We monitor, maintain, and extend on a monthly roadmap you control. Everything is documented, your data leaves with you on request, and if we part ways we plan a clean handover.
How pricing works
Priced in writing, before you commit.
Cost depends on what you already run and what we build, so we price after the systems map, not before. The first build is a fixed-scope proposal with the figure in writing. Running and extending it after launch is month to month.
Questions we get asked.
How much does custom business software or AI automation cost?
Cost depends on what you run today and what we build, so we price each engagement after a short systems review rather than on a webpage. We scope the first production slice deliberately small and real, and you get a written, fixed-scope proposal with the exact figure after the consultation and systems map, before you commit to anything.
How fast can we be live?
The first production slice typically ships in weeks, not quarters, because we scope it deliberately small and real. What we will not do is promise a date before we have seen your systems. That is what the consultation is for.
Which AI models do you use?
Best-in-class commercial models where they earn their place. We have no "proprietary AI," and we would distrust anyone who claims theirs. Our value is the system around the model: validated inputs, schema-checked outputs, confidence thresholds, and human review queues.
What happens when the AI gets something wrong?
It gets caught. That is the design. Every AI step is checked on both sides: clean data going in, validation and business-rule checks coming out, and anything the system is not sure about lands in a human review queue. Wrong answers route to people; they never flow silently into your books.
Are you HIPAA / SOC 2 certified?
Straight answer: we are not SOC 2 certified. That audit is on our roadmap, and we will not claim it until it is done. We sign BAAs for health-data work, and we will walk you through our actual architecture and controls, including what is still on our roadmap, so you can assess it yourself.
Can we see real work?
Yes. Our case studies describe systems running in production right now. Client names are shared only with the client’s permission, but under a mutual NDA we will walk you through live architecture, approval workflows, and the actual running code during the consultation.