I start an AI implementation with one process. I check that it pays off before I build anything.
I start with one job that keeps coming back in your company. I go through it step by step and answer in writing whether software should take it over. You do not need any technical knowledge for that conversation.
I examine one task in your company. You receive an assessment of whether AI is worth using and a proposal for a first implementation.
How to start
You do not have to prepare anything. Two sentences about the work that takes up most of your time are enough. If it turns out there is nothing here worth building, you will at least know where not to spend money.
Worth reading first
How the audit works, and when a chatbot on a company website pays off, are two separate articles on the blog.
The same four steps every time. Choosing a tool comes after the process is on paper.
I pick a single job where the stake is clear: time, how often it repeats, what an error costs, or what a customer feels. Only one, because a pilot that touches everything is hard to judge afterwards.
I write down the data it uses, the tools it passes through, the decisions inside it and the exceptions that break it. This helps me decide where AI could help and how to check its output.
I connect the data and tools, define how results will be checked and decide where a person must approve an action. The initial version handles a limited set of cases.
I run it on cases that have already been handled and compare what it did against what a person did. It gets a second job only once the first one holds.
Example flow
A supplier invoice reaches the inbox. The system reads the fields, checks them against the order, updates the CRM and routes mismatches to a person for approval.
Somebody opens an email, reads four numbers off a PDF, compares them with what was ordered, types them into another system and files the PDF. Nobody notices the work until something goes wrong.
Each part of that flow does a different job. A model reads the document, because it copes with a badly scanned PDF better than ordinary code does. Ordinary code does the comparing and the writing, because a comparison has to give the same answer every time. The last part matters most: when the invoice and the order disagree, the flow stops and shows the case to a person, and those are the only cases that need anyone’s attention.
First I run the flow over invoices that have already been processed and compare its results with what was done by hand. It handles live documents only once the two match.
Chat assistants, document processing, reporting and connections to company tools. The task assessment determines which ones you need.
Where this already runs
Asystent PV is my own chat assistant for solar installers, live at asystentpv.pl. It answers customers under the company’s name, says when it does not know and passes the question to the office. You can ask it something right now. The same build goes onto another company’s offer, prices and questions.
View the Asystent PV projectFive commitments you can hold me to.
Money leaving, a contract, an answer to a customer that cannot be taken back: the flow prepares it and a person releases it. That step is part of the flow’s code, so the model cannot talk its way past it.
Before a flow gets more work, I measure on your own examples how many cases it handled without a person and how many it got wrong.
I build inside the systems you already have: your CRM, your mailbox, your server.
Every automated action is written to a log a person can read afterwards. When something looks off, you and I start from the same record.
If the audit finds AI would not take real work off anyone, the note says so and suggests what would help more. You read it before any build starts.
The tools I reach for most often.
Where AI is not worth it
Plenty of steps do not need a model at all. If a rule with three conditions gives the same answer every time, it beats a model that is right most of the time, and it never surprises anyone on a Monday morning. Where the job is small enough that custom code would be the wrong answer, I wire it up in Zapier or Make and write nothing. And where the honest fix is a better form, a tidier spreadsheet or one fewer step, I will tell you that.
Projects you can see running. Each write-up shows what was built and how it works.
AI implementation quote
Say what AI should do at your company. I reply with a price, or with the questions that have to be answered first.
