Systems architecture for the AI era
Your business runs on systems AI can’t read.
We fix that. Old systems in. Clean data layer. Claude working for you.
We wrote the book our AI works from: our own Airtable skill
Sound familiar?
The ERP is old enough to vote.
The real numbers live in four spreadsheets and one person's head.
Someone on the board just said “we should be using AI.”
Pointing AI at that mess produces confident nonsense: the demo rises, production drifts. The fix is one layer down.
The bridge, in one picture
Today
Your old systems
Legacy software. Spreadsheets. Inboxes. Memory.
What we build
One clean data layer
Every fact in one place, current, and owned by your team. Built on Airtable.
Then
Claude, working for you
Connected to your systems, trained on your business, running as agents on schedules you set in plain language.
We verify. We don’t assume.
Tested first
We caught a vendor's own manual being wrong about their product. Before building on it.
3 flaws
found by our pre-launch review in work that looked finished. Fixed before anyone paid for them.
Monthly
every system we ship gets re-tested on a schedule. Facts age; ours get checked.
Our differentiator
We wrote the book our AI works from. Literally.
Generic AI gives generic advice, and generic advice breaks real systems. So we built our own Airtable skill: a tested, versioned body of knowledge that turns Claude into a senior consultant on the platform our data layers run on.
Why: the public knowledge was wrong. Documentation lagged reality, tutorials repeated stale limits, and AI models repeated the tutorials. The only cure was testing everything against the live platform and writing down what was actually true, with dates.
How: parallel AI researchers swept documentation, community practice, and our own project archives. Every claim that could be tested was tested live. A review team attacked the result until a security gate stopped finding holes. A routine re-tests it monthly.
Researched. by parallel AI agents across every source that mattered, including our own delivery archives
Live-tested. against the real platform. Where the vendor's docs and reality disagreed, we shipped reality, dated
Attacked. by adversarial review until releases stopped being blocked. Three flaws never reached a client
Self-updating. an automated routine re-verifies the volatile facts every month, so it never quietly goes stale
Every engagement runs on this discipline. The full build story: every sentence was true, and it still was not safe
Three ways in
Fixed scope. Fixed price. Few clients at a time.
AI Readiness Architecture
$4,000from
Two weeks. You get the map.
- Where your data actually lives
- What AI can do with it today
- A sequenced roadmap you keep
The Bridge Build
$15,000from
The flagship. We build the whole bridge.
- Legacy systems connected to one data layer
- Claude trained on your business
- Your words become prompts, schedules, and agents
AI Operations Partner
$3,000from, monthly
We stay on. It keeps getting better.
- New automation every month
- Facts re-verified continuously
- Limited seats
Built for real operations
Security services. Paper and chat chaos became automated shift reports and client-ready documents.
Travel logistics. Billing that silently skipped records now runs on watched inputs and frozen snapshots.
Memberships. Payment-to-pass automation that is safe to re-run and was enabled one piece at a time.
Real estate. Double-counted money flows made structurally impossible. One set of numbers.
Latest news
All postsSystems older than your AI ambitions?
One email. A real conversation about your problem. Then a fixed-scope proposal, and whatever the solution needs, managed end to end.
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