AI Development

AI automation services, for the workflows your team still does by hand

Most of what a business calls AI automation is one of three jobs: reading documents, deciding the next step, and writing the result into a system someone used to update by hand. We build them into the workflow you already run, with the review step and the cost per run written down before the code. One platform we shipped cut manual processing by 87% at 99.2% extraction accuracy, in production in 10 weeks.

$15,000–$30,000 for one workflow added to a system you run, 2–4 weeks · $40,000–$120,000 for a full AI product · or AI engineers on your team from $4,000 a month

Pick the first workflow

The three shapes of AI automation

Almost every workflow worth automating is one of these, or two of them in a row. Each has its own page with the detail.

Documents in

Invoices, customs papers, contracts and email attachments read into structured data, validated against your reference data, and queued for review when the model is unsure. AI document processing.

Decisions in the middle

An agent that triages, looks things up and calls your tools, with an evaluation set and a human checkpoint where a mistake would cost money. AI agents.

Systems updated at the end

The result written back into the ERP, CRM or ticketing system the team works in, so nobody copies it across by hand. AI integration.

Which workflow to automate first

The order the logistics platform was built in: the highest-volume flows first, because that is where the hours are.

It happens many times a day

Volume is what turns minutes saved per item into a business case. A workflow that runs twice a week rarely pays for its evaluation set.

A person could explain the rule

If the people doing it today can say how they decide, the system can be checked against that. If they cannot, start by writing it down.

The answer can be checked

Extraction, classification and routing have right answers. Those are the cases a golden dataset can score from week one.

The data is reachable

The documents and the systems are ones you can grant access to. Where data cannot leave your boundary, the pipeline is designed self-hosted, which changes the price, so say it on the first call.

What has to be true before it runs unattended

The difference between a demo that automates something and a workflow you can stop watching.

An evaluation set

Real cases with known answers, built before the pipeline, so quality is a number you regress against. Our 99.2% is that number.

A threshold and a reviewer

Below a confidence threshold the item goes to a person with the source highlighted, rather than into your system.

A cost per run

What one item costs to process at your volume, written down before the build. On the platform we measured, about $0.011 per answer.

What AI automation costs, in one paragraph

The bands are the ones on our pricing page.

One workflow added to a system you already run is $15,000–$30,000 over 2–4 weeks, quoted as one fixed price after a discovery call, with a written scope inside 48 hours. A full AI product with its own interface is $40,000–$120,000 over 8–12 weeks. Running it is a separate and much smaller number: about $0.011 per answer on the platform behind this page. Where a project lands inside a band is decided by how many systems the result has to reach and how ready the data is, rarely by the model.

When automation is the wrong first buy

Three situations where something smaller gets you further, and we would rather say so on the first call.

The process is still changing

Automating a rule that changes weekly means rebuilding weekly. Settle the process, or put AI engineers on your team who change with it.

Nobody can say what correct is

Then there is nothing to evaluate against. A few hours of AI consulting to define it costs less than a build that cannot be accepted.

The volume is small

A task done a few times a week rarely repays the evaluation work that makes automation safe. A better tool or template usually does.

Common questions

What operations leads ask before the first workflow is chosen.

The ones with volume, a rule a person could explain, and an answer you can check: reading invoices, customs papers or contracts into structured data; triaging an inbox or a ticket queue; and writing the result back into an ERP or CRM someone used to update by hand. Work whose rule changes every week, or whose correct answer nobody can define, is a poor first candidate.
One workflow added to a system you already run is $15,000–$30,000 over 2–4 weeks at a fixed price; a full AI product with its own interface is $40,000–$120,000 over 8–12 weeks. Running it is a separate, much smaller number: about $0.011 per answer on the platform we measured. If you would rather have the engineers on your team, that is $4,000–$7,000 per engineer per month.
It replaces the copying, not the judgement. On the platform behind our figures, manual handling fell by 87% and analysts moved to exceptions and review rather than retyping documents. We do not claim the system is more accurate than the people it took work from: nobody measured the manual process before it was replaced.
With three things built before it runs unattended: an evaluation set of real cases with known answers, a confidence threshold below which the item goes to a person, and an audit trail of what the system read and why it decided. The 99.2% extraction accuracy we publish is that evaluation set’s number, not a demo.

What this has shipped

The automation behind the figures on this page, published as a case study.

Have a workflow your team still does by hand?

Tell us what it is, how often it happens and which systems it touches. We come back with a fixed scope and price in writing within 48 hours of the call.

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