On your systems, with your data, and with the AI tools you already use.
What we do
In mid-sized and large companies, on the systems they already have.
A large share of office work is moving information from one format to another: from email to the ERP, from a PDF to a spreadsheet. Current models read documents, images and photos, which makes it possible to automate processes that could not be automated before.
ExampleA media group's supplier invoices arrive by email and are posted automatically.
A custom application used to cost six figures and take nine months. Today it is built in weeks, on the systems you already have. Now is the time to replace the spreadsheet someone maintains next to the ERP, or the per-seat SaaS that does not fit how you work.
ExampleA capacity and pricing tool for a concert promoter, and our own Backoffice.
The documentation nobody reads and what only three people know, turned into answers and, increasingly, actions. Along the way we almost always discover how little was written down, organized or kept up to date.
ExampleTenders at a medical technology company and IT support at an industrial group.
Your ERP and CRM stay where they are. Around them we build the software that knows your processes, your rules and your data, so the AI you already use can work across the whole company.
Use cases
The problem
At a food group, following each new hire took many manual steps, and nowhere showed the status of all of them.
What we built
An agent in Teams that creates each new hire's record, checks in with them during their first weeks, answers from the process documentation and opens tickets when something is missing.
How we make it reliable
The problem
An industrial group receives IT support requests by chat, and each one had to be understood, logged and assigned by hand.
What we built
An agent that understands the request, opens the ticket in the ticketing system, classifies it and, if the solution is already known, replies with the steps.
How we make it reliable
The problem
A concert promoter receives thousands of inquiries on every tour, and the customer service team answered them one by one.
What we built
A system that finds the answer in their documentation and prepares a draft that an operator reviews before it is sent.
How we make it reliable
The problem
A hospital equipment company bids on tenders in several countries, and deciding whether each one was a fit meant reading the whole tender document.
What we built
A system that extracts the requirements from each tender document and matches them against the company's catalog, so the team can decide early whether bidding is worthwhile.
How we make it reliable
Blog
What we believe comes after the first wave. We explain it in our articles.
About us
Napptilus is a technology company founded in Barcelona in 2004.
We work with mid-sized and large companies, almost always starting with a single division and growing from there, and we write about what we learn on each project.
We collaborate with professors from the Universitat Politècnica de Catalunya and the CSIC.
Tell us what you want to solve. A member of the team will reply within 24 business hours.
