AI workflows in New York City
Automate the work nobody wants to describe at length.
Not AI for the demo video. We automate the steps that actually cost hours — intake, sorting, drafting, summarising, checking — with a model doing only the part it's genuinely good at.
The useful automations are rarely exotic. A form arrives, it gets read, categorised, checked against what the business already knows, and routed to a person who only has to decide. Every step is boring. Together they're four hours of someone's day, per week, and they are almost always the same four hours.
We build those. Which means: mapping the real workflow before automating it, keeping a human in the loop where a wrong answer is expensive, and instrumenting it so you can see what it did and why. If a step doesn't need a model, it doesn't get one.
Sounds like you if
You already know something is wrong with it.
- A capable person spends part of every day copying between systems.
- The team's real process lives in one spreadsheet only they understand.
- Invoices, applications, or orders get typed in from documents.
- The same report gets assembled by hand each week and nobody trusts it.
- Everyone agrees the process is wasteful and it still has a champion.
- A project failed because the workarounds around a system were invisible.
What the work covers
What you get, in plain terms.
Document and message intake
Reads what arrives, pulls out the fields the business actually needs, and puts them where the process expects them.
Triage and routing
Sorts, prioritises, and hands off — with the rules written down where a human can change them.
Drafting with a person approving
Emails, responses, and summaries drafted for review. The model proposes; your team decides.
Reporting that assembles itself
The weekly digest, compiled from the systems that already have the numbers, with disagreements flagged instead of smoothed over.
Model evaluation
Tested against your real examples before it touches production, because the demo set flatters everyone.
Guardrails and fallbacks
Confidence thresholds, retries, and a clear path to a human. An automation nobody can audit is a liability with a nice dashboard.
Who this is for
Worth a call when the answer can't wait for a bigger team.
- Operations teams running on manual steps that outgrew the headcount.
- Service firms where intake, drafting, and summarising eat the day.
- Founders automating their own company before automating a client's.
Questions we get asked
Before you email us about ai & automation.
What if it gets it wrong?
Then the step it can get wrong is the one a person approves. We set the confidence threshold, log every decision, and start automations in the background so you can watch before trusting them.
Do we need to move our data to use AI?
No. We build against the systems you already run and call models from the provider that fits the job. Nothing needs a migration to benefit from an automation.
How do we know it saved anything?
Every automation reports what it did. If a month goes by and the number isn't compelling, the honest answer is that the workflow wasn't worth automating — we'd rather hear that than invoice for it.
AI workflows & automation usually starts with fifteen minutes.
Tell us what is stuck. If ai & automationis the wrong answer, we'll say so and point you at the right one.
Often working alongside