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Capitole, a technology consultancy with a presence in Spain, Portugal, Belgium and Luxembourg, is launching Capitole Lab, its R&D unit specializing in software engineering, artificial intelligence and digital product design. Capitole Lab was created to help companies go beyond traditional development and innovate with a measurable impact on their business.
The unit will support every project from the initial idea through to validation in real industrial environments. To do so, it will work hand in hand with companies, technology centers, universities and consortiums, under the motto Think. Design. Deliver.
Four areas of focus
Capitole Lab focuses on four areas:
- Generative AI: systems that create new content by learning patterns from data, rather than simply analyzing it.
- Digital twins: virtual replicas that simulate and predict real-world outcomes.
- Autonomous agents: AI systems that plan and act independently to complete tasks, with minimal human intervention.
- Real-time data: live data streams processed instantly through explainable AI pipelines to support decision-making.
Impact over trends
Capitole Lab is built on the idea that meaningful AI is AI that demonstrates its impact, not AI that follows the latest trend. It already works with hospitals to improve the prediction of cardiovascular disease through machine learning. It also collaborates with industrial companies on deploying digital copilots that provide full visibility into their production plants. Its results are published in scientific papers and presented at international conferences.
A multidisciplinary team
The Capitole Lab team combines research, engineering and product profiles, covering the entire journey of a project, from the first conversation with the business unit to a solution running in production:
- Technical and R&D leadership: coordinates the work across data science, machine learning and generative AI. It also drives grant and funding applications so that the most ambitious projects have more room to move forward.
- AI research: profiles with a scientific background, such as applied physics, who develop AI solutions for fields as varied as healthcare and language models. They pay particular attention to explainable AI, so that its power comes with transparency and reliability.
- AI engineering and autonomous agents: engineers who design systems capable of planning, using tools, automating complex workflows and verifying their own results. Their developments include assistants that help sales teams prepare for client meetings and systems that spot differences between technical drawings of car engine parts.
- Product innovation: specialists who bring ideas to market with the user at the center, through discovery, experimentation and data analysis, on the premise that an idea is neither good nor bad until it has been validated.
This combination of profiles shares a single goal: to turn emerging AI capabilities into robust, reliable tools that people actually use in their daily work.
