AI does the reading. Your team does the deciding.
We build AI workflow automation into the systems you already run — reading the inquiries, documents, and requests that arrive every day, and turning them into drafts, records, and decisions your team approves rather than produces. Built on n8n, Make, or Zapier.
Systems we have designed and built
Each one shows the same thing: where AI does the reading and judging, where fixed rules take over, and where a person stays in control.
Opportunity scoring with reasons
Inconsistent inquiries become a consistent qualification decision — with the evidence recorded, and anything unclear routed to a person.
See how it works →02Answers from your own documents
Questions asked in plain language, answered from your approved documents, with the source of every statement shown.
See how it works →03Supplier and product qualification
Thousands of inconsistent records scored in two stages, every rejection reason kept, and nothing published without approval.
See how it works →Work your team is doing that a machine should be finishing
The same information, entered twice.
An inquiry arrives as free text, and someone re-enters it into the system that runs the job, then again into the one that raises the invoice.
Documents assembled by hand from material that already exists.
Reports, client updates, briefs, and proposals written from scratch each time.
Long documents read for the few points that matter.
Contracts, tender packs, meeting recordings, and reports read end to end so that three decisions can be extracted.
Requests read and sorted one at a time.
Inquiries, tickets, and applications categorized by hand and answered from something close to a standard reply.
Each of these has a step in it that needs judgment about language — which is exactly where AI does work that rule-based automation cannot.
Book a 30-minute callWhy this is safe to put near work that matters
AI and your rules stay separate.
The criteria you set are applied as fixed rules. An AI interpretation cannot quietly override a must-have.
Every decision carries its reasons.
Not a number, but the evidence behind it, the risks identified, and what information was missing.
Uncertainty stops the line.
Low confidence, contradictory information, or a missing field routes to a person with an explanation attached.
Nothing fails quietly.
A failed step becomes a visible exception. It never becomes a wrong answer sitting in your system looking correct.
Decisions stay inspectable.
What went in, what the AI proposed, what was decided, and what a person changed — recorded and reviewable.
Most AI demonstrations show the happy path. The engineering is in everything else.
How we work →AI implementation in three stages
Find out what is worth doing
Two review engagements, depending on breadth. The AI Readiness Audit covers up to three processes in two to three weeks. The Deep Audit covers six to eight across teams, with volumes measured from your own system data. Both produce a ranked plan and a list of what to leave alone.
Build it properly
AI Workflow Implementation in three sizes — Lite, Standard, Advanced. Two to ten weeks depending on scope. One workflow built end to end, connected to the tools you already use, tested against your own historical work.
Keep it running
AI Workflow Optimization Retainer in three levels — Lite, Standard, Advanced. Monthly and rolling. Maintenance, quality tuning, and improvement, so output stays reliable as the work coming through changes.
What we will not automate
Every audit includes a list of what to leave alone. It is usually the section people find most useful.
- We will not use AI where a simple rule would do the job more cheaply and more reliably.
- We will not automate something because it is technically possible. It has to repay the effort.
- We will not remove a person from a decision that needs judgment.
- We will not replace the systems you already run. We work with them.
- We will not leave you dependent on us. Everything is documented and handed over.
The technology we build with
We build with Claude and OpenAI models for the steps that involve reading, writing, and judgment, connected through Make, n8n, or direct connections to the systems you already run — Microsoft 365, Google Workspace, HubSpot, Airtable, Xero, QuickBooks, and most mainstream business software.
You keep your systems. Nothing moves to a platform of ours.
See the workflows in detail
Full write-ups of all five systems — what each does, where AI is required, how it runs stage by stage, and what happens when it is unsure.