Artificial intelligence applied to your processes and data
Useful AI is usually found in what the company already has: invoices, tickets, policies, sales history. We work on that. No need to replace your current system.
Institutional definition
What we do with your data
This line applies artificial intelligence to processes and data the company already runs. Different from a support chatbot, different from software built from scratch. Typical work: querying your own databases, summarizing documents, classifying tickets, supporting a decision with real history.
Matriz de viabilidad
Signs this is the right page
- You have systems running that nobody queries well.
- The knowledge lives in PDFs, emails, or folders.
- You want an internal assistant, not a customer-facing one.
What we deliver
What we deliver
01
A system that answers with the cited source
02
Permissions
03
Usage logging
04
An "I don't know" criterion
05
Supporting cases
Normsy (study with 1,021 participants) when the problem is judgment and modeling, not just information retrieval. The work with an international organization when the corpus is institutional and large.
FAQ
Frequently asked questions
Do we have to migrate everything to a data lake?
Not as a first step. First you pick a process and a source.
Do you train a custom model?
Sometimes good retrieval is enough. Training is a decision, not a default.
If the data already exists and isn't being used, the project isn't "doing AI".
It's putting it to work.