Where we explore today
what we’ll apply tomorrow
The AI Lab is our experimentation environment: applied AI, automation, new workflows and systems that we test before integrating them into real projects.
Our AI ecosystem
We work with the most advanced AI models, but what matters is how we integrate them to solve real problems.






A lab to validate
what’s really worth it
AI is changing how software is built and how teams work. But not everything new deserves to go straight into production.
The AI Lab is our controlled environment for exploring and validating which technologies add real value before applying them to projects.
We research tools, automations and workflows. Some get integrated. Others get discarded.
And that’s part of the work too.

Applied AI
Automation, copilots, analysis and AI-assisted workflows.

Testing
Technical and functional validation before scaling solutions.

Integrations
New ways of connecting tools, context and operations.

Evolution
Systems that learn, iterate and improve with real use.
Active explorations
Active experiments aimed at real operations, automation and smart integration.
Integrated
Document automation
Assisted processing, classification and generation of documentation.
Validation
AI-assisted QA
Validation of flows, test case generation and support with repetitive testing.
Exploration
RAG & Knowledge Retrieval
Contextual search across documentation and internal knowledge.
Integrated
AI Workflows
Automation of operational tasks and internal processes.
Validation
Assisted code review
Contextual support in code review and early error detection.
Exploration
AI Support
Exploring assistants for technical support and internal operations.
We’re not looking to use AI for the sake of it.
We want to understand what really improves the work.
AI Lab principles
How we decide what to integrate and what to discard.
01
Experiment before integrating
We test in controlled environments before applying anything in production. No experimenting directly on real projects.
02
Validate before scaling
We measure real impact and operational viability in each case. We don’t assume a tool will work just because it’s new.
03
Automate without losing judgement
AI assists, but technical and strategic decisions remain human. Teams stay in control.
04
Improve processes, don’t complicate them
We only integrate what reduces real friction. If it adds complexity without clear value, it’s discarded.
05
Keep human oversight
Teams understand how the automated workflows work and can step in and adjust them when necessary.
06
Keep evolving
We learn, adjust and discard what doesn’t work. Experimentation never ends.
AI Lab news
What we’re testing, validating and learning.

AI / News
3 min
Ibérica Labs returns to WATA Factory on 4 June: AI at the centre of the discussion
On 4 June, we will host a new edition of Ibérica Labs at WATA Factory – an internal event where different teams will share research, ideas and new ways of working around some of the technologies that are currently shaping the evolution of the industry the most.

AI / News
4 min
Ibérica Labs at WATA Factory: from Kubernetes to AI-assisted workflows
A few days ago, we held a new edition of Iberica Labs at WATA Factory, a day on which we once again deliberately set aside time for something that is often difficult to find in everyday work: learning, researching and sharing knowledge across teams.

AI / News
5 min
Artificial intelligence in technology companies: WATA Factory’s approach for the coming years
A few days ago, we brought the entire WATA Factory team together at the office to share the company’s strategic plan for the next two years. A large part of the conversation revolved around how the industry is changing and around something that, whether we like it or not, is already beginning to directly affect […]
Let’s talk
Processes, automation, product or new ideas.
We help you find the best way to take them to production.

Quick response

No endless processes

Technology with judgement

We keep it clear








