The team behind your AI transition.

Gleb Dirzu

Founder & CEO · Your Chief AI Officer

• AI strategy
• Business models
• Agentic AI
• Return on investment

Gleb has built and run businesses and AI systems across very different models and sectors, from investment-fund operations to health and wellness and live events. That range is the core of his method. He has seen what makes money in each kind of company, what wastes it, and why the same AI tool succeeds in one business and fails in the next.

He combines this with a deep, hands-on command of modern AI: language models, agentic AI, the wide range of applications built on them, and how to choose and combine models for each task. He directs teams of engineers and AI agents himself, so his plans rest on what can actually be built. For each company he decides where AI pays back fastest, where it should not be used yet, and in what order to move. The result is a plan built for a fast return on investment and a safe deployment, inside a long-term strategy that keeps the company improving year after year.

Dr. Luis Pizarro

Head of Compliance & AI Governance

• EU AI Act
• AI governance
• AI standards
• Executive training

Luis has spent 25 years in artificial intelligence, from hands-on engineering and applied research to national and corporate AI strategy. In leadership roles at EY and Huawei he built AI platforms and led teams of more than 35 engineers and researchers, delivering multi-million-dollar sales growth in regulated sectors: financial services, healthcare, oil and gas, mining, telecommunications, critical infrastructure, logistics and the public sector. He represents the UK, through BSI, on the ISO/IEC and CEN/CENELEC committees that write the international and European AI standards.

He advises government ministers and executive teams, turning regulation such as the EU AI Act into governance frameworks and technology that can be deployed with confidence: risk classification of each use case, audits, conformity assessment and certification, and AI due diligence for investors. He has built training programmes and helps companies stay up to date with the latest Spanish and EU requirements through one-to-one work with executives, corporate workshops and company materials. His focus is AI that creates measurable value and that a board, its auditors and the regulators can trust.

Dr. Luis Cadarso Morga

Principal Advisor · Optimization & Complex Systems

• Mathematical optimization
• Planning and scheduling
• Decision support
• R&D leadership

Luis has built his career where mathematical optimization meets real operations: integrated planning of air and rail transport, recovery from disruptions, network design, and guidance, navigation and control systems. He has published more than 30 articles in international journals and over a hundred conference contributions, held research stays at MIT and Erasmus University, and taken part in numerous competitive national and international research projects.

His work goes well beyond research. He has directed technology-transfer contracts with companies and public administrations, applying optimization and AI to planning, mobility, intermodal transport, autonomous systems, and mission planning and logistics for defence and security. He leads research groups and evaluates R&D projects. A Doctor in Aerospace Engineering, he is a Full Professor (Catedrático) at Universidad Rey Juan Carlos and Director of the European Institute for Aeronautical Training and Accreditation (EIATA). His strength is turning open, messy business problems into rigorous models that respect every constraint, account for uncertainty and balance several goals at once.

Dr. Víctor M. Tenorio Gómez

Lead AI Scientist · Generative & Agentic AI

• Agentic systems
• Private language models
• AI security
• Explainable AI

Víctor's doctoral thesis won the 2026 best doctoral thesis award of the IEEE Spain SP/COM Joint Chapter, which highlighted its potential for technology transfer. He has published more than 15 papers at leading venues, including NeurIPS, ICASSP, the Asilomar Conference and IEEE Transactions on Signal Processing, and works with research groups at TU Delft, Rice, Dartmouth, Johns Hopkins and Rensselaer Polytechnic Institute. His research focuses on models that stay reliable when data is noisy, incomplete or uncertain, and that state how sure they are.

He also spent two and a half years at Deloitte in cybersecurity, on identity and access management for major national and international banks, including a financial-markets operator, and for multinational retailers. Today he designs multi-agent systems on open-source language models hosted inside the client's own infrastructure, so sensitive data never leaves it, with minimum permissions per agent and every action traceable. He co-founded a technology company where he led satellite-vision, AI drone-guidance and production machine-learning projects, leads R&D contracts with companies and supervises three PhD students. He is an aerospace and telecommunications engineer, a Doctor in ICT and an Assistant Professor at Universidad Rey Juan Carlos.

Dr. Óscar Escudero Arnanz

Lead AI Engineer · AI Platforms & MLOps

• AI in production
• Cloud and GPU
• Document search (RAG)
• Explainable machine learning

Óscar takes AI from pilot to production. He designs AI platforms on Google Cloud and Vertex AI, Kubernetes and vLLM, serves open-source models, and handles automated deployment, monitoring, versioning and GPU sizing. His specialty is what breaks between a proof of concept and a real system: speed, many users at once, scale, security and cost, and moving safely from testing to live use.

His doctoral research, in ICT at Universidad Rey Juan Carlos, built explainable machine-learning models on intensive-care data, including prediction of antimicrobial resistance, a field where every prediction must be accurate and justified. In generative AI he works on document-search systems (RAG), agents and side-by-side evaluation of language models. He designed and evaluated an AI assistant for antimicrobial-resistance research, judging not only the quality of its answers but also cost, speed and model choice: exactly the criteria a company needs when it picks its models. Drawing on his teaching experience, he bridges researchers, engineers, architects and business people, and guides client teams from the first experiment to production.

Fernando Real Rojas

AI & Optimization Engineer · Automation & Decision Tools

• Process automation
• Optimization
• Decision tools
• Systems integration

Fernando received the Extraordinary Award for the best academic record in his double degree in aerospace and telecommunications engineering, and holds a Master's in AI Research. His research covers convex and bilevel optimization, surrogate models, and planning, design and resource-allocation problems. He has contributed to work presented at NeurIPS and the INFORMS Annual Meeting, and takes part in research projects at Universidad Rey Juan Carlos on Industry 4.0 and AI-assisted optimization for transport.

In practice, he maps how a company really works (its business rules, limits and goals) and turns it into formal models and software: from automated workflows to decision-support, planning and resource-allocation tools connected to the company's APIs, databases and existing systems. He is most valuable where a prediction is not enough and the real question is which action to take, how to assign resources or how to optimize a process under constraints. He builds modular components that slot into the client's everyday processes, and has applied the same methods to defence and other critical environments.

Guillermo Megías Areas

Software, DevOps & Mission-Critical Systems

• Mission-critical software
• DevOps and continuous delivery
• Systems architecture
• Satellite navigation

Guillermo is a telecommunications and aerospace engineer specialised in satellite navigation (GNSS) and in building and running mission-critical software that delivers real-time services for defence and large organisations. He works on large, complex platforms where development, infrastructure and operations must act as one system, with strict service-continuity requirements, many integrated components and changes that must be made without stopping anything.

He designs systems end to end, connecting software, infrastructure, interfaces, operations, requirements and deployment so every part evolves consistently. He brings DevOps practice, automation and continuous integration and delivery, working in agile teams under the SAFe framework, where software is designed not only to be built but to be deployed, monitored and maintained repeatably and safely. His background in real-time navigation and processing, plus academic training in AI, machine learning and algorithm optimization, lets him spot the dependencies that usually cause trouble late in a project, and makes AI solutions robust enough to run inside high-availability platforms.