Responsible use of AI
How we apply artificial intelligence in our projects: transparency, human oversight and limits.
Courtesy translation: the Spanish version prevails
Read the binding Spanish version
Informative text — this is not legal advice
What we automate — and what we don't
Before automating, we weigh impact and risk. If a process is not worth automating —because of volume, exceptions or the cost of an error— we say so before starting. No project begins without agreeing on what will be measured and what stays out of scope.
Human oversight
Every delivered workflow defines what the machine decides and what a person decides. Drafts written by AI are reviewed by a person before they reach an end client; decisions with financial or contractual impact are always human. The ultimate owner of every workflow is a named person, not a system.
Transparency with end users
When we deliver an assistant or chatbot, it identifies itself as such to whoever uses it. The European AI Act (Regulation (EU) 2024/1689, Article 50) requires informing people that they are interacting with an artificial intelligence, and the systems we deliver comply by design.
Known limits
A language model can be confidently wrong. That is why the agents we build answer only from controlled sources, are allowed to say "I don't know", and escalate to a person below a confidence threshold. Even so, no system is infallible: workflows log what they do so it can be audited.
Client data in projects
Workflows, credentials and data live in the client's accounts, not ours. We choose providers and processing regions together with the client, minimise the data that reaches third-party models, and never use client data to train models.
Measurement and reversibility
Metrics are agreed before building and reviewed afterwards. Clients can switch off any automation and take their workflows and documentation with them at any time: no hidden dependencies.
Last updated: August 15, 2026.
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