AI at work
Your team spends hours reading, sorting and summarising by hand
We put AI to work on specific tasks, such as reading applications, documents and emails, with clear rules and a person making the call.
Who it’s for
For teams that read lots of similar documents by hand: job applications, tender documents, client emails, news. The work repeats and slows down the response.
Signs you need this
- Screening applications or requests takes longer than the reply should.
- Someone has to read long documents looking for exceptions, and sometimes they go unread because there’s no time.
- Your team has tried AI tools, but they stayed in a chat window, apart from the work.
What we do
- We pick one specific task and measure how long it takes today.
- Fixed rules handle the obvious cases. The model only sees what’s left.
- Every decision is logged with the reason, so it can be reviewed.
- A person decides the unclear cases.
- The system keeps learning. Every correction and every new case goes into a company knowledge base, so the system gets better with use and doesn’t depend on us for that.
- The AI account is in the company’s name.
A real case
At an IT services company with over 100 people, every new application is read against the job requirements. Response time to candidates went from about 33 hours to 24 minutes, and 70% of applications no longer need to be read by anyone. The team talks to the interested candidates first.
At a construction company with fewer than 10 people, an assistant reads the documents for each new tender and flags anything outside the company’s standard, with the clause and the page.
Frequently asked questions
Will the AI make decisions on its own?
Only the ones we agree on, and every one is logged with the reason. When there's doubt, a person always decides.
What if the AI gets it wrong?
That's why there are fixed rules before the model, a log of every decision and a person for the unclear cases. Every correction becomes part of what the system knows.
We've tried AI and it didn't stick. Why would this be different?
Because the AI is connected to where the work happens, on a specific task, instead of sitting in a separate chat. We test it on one person's work first and only then roll it out to the team.
Does the solution always include AI?
No. First we sort out the process and use what your tools already do. AI comes in when it pays off.
Tell us where your team loses time.

Prefer to write? marta.matos@withzeno.com