General information

Hosting Organisation

Gradiant
Address

Estrada do Vilar, 56-58
Web

https://gradiant.org

Contact Info:

Phone

(+34) 986 120 430
Email

gradiant@gradiant.org

Description

Gradiant, Spanish ICT technology centre, aims to improve the competitiveness of companies by transferring knowledge and technologies in the fields of connectivity, intelligence and security. With more than 250 professionals and 14 applied patents, Gradiant has developed more than 800 different R&D&i projects, becoming one of the main engines of innovation in Galicia. In 2025, Gradiant’s turnover reached 17 million euros, working with more than 400 clients in 30 countries over the past 17 years.

The commitment with quality is a constant from the beginning. Today Gradiant has certificates on Quality Management Systems UNE-EN ISO 9001:2015, Innovation Management Systems UNE-EN-ISO 56002:2024 and Information Security Management Systems UNE-EN ISO/IEC 27001:2022.

After sixteen years of activity, Gradiant is positioned as a technology partner for the industry, oriented to their needs in the field of ICT, contributing their national and international experience in technologies for security and privacy; processing of multimedia signals; Internet of Things; biometrics and data analytics; and advanced communications systems.

Summary of Research Services

The main research areas at Gradiant are:
Multimedia analysis: research into digital file manipulation and video analytics for the monitoring of maritime and border areas.
• Cloud-Edge Continuum: research into cloud technologies, GPU and CPU computing, FPGAs and neuromorphic computing.
• Advanced Data Management: integration of unstructured information; we participate in the development of interoperable data spaces aligned with European frameworks; we develop Privacy-Enhanced Technologies, such as homomorphic encryption for performing operations on encrypted data.
• Applied Artificial Intelligence: AI applied to cybersecurity, combining behavioural analysis with process mining and deep learning; decentralised AI solutions; and multimodal AI integrating text, video, audio and images.
• Data security: design of secure systems for IoT processes and embedded systems; data analysis for protection against anomalies; expertise in federated learning and machine learning.
• Autonomous systems: we develop local positioning systems to provide location services and implement algorithms.
• Communications systems: Development of SIGINT technologies capable of detecting, identifying and analysing emissions in the radio spectrum.
• Micro- and nanoelectronics technologies: Development of custom hardware such as ASICs, SoCs and FPGAs
• Cybersecurity technologies: We incorporate user behaviour analysis, process mining and reinforcement learning.
• Language Technologies: We investigate text generation and analysis in natural language processing for information extraction and classification.
• Quantum Technologies: Covering both software and hardware for application in quantum sensing, metrology, computing and communications.
• Photonics Technologies: Developing photonic signal and processing circuits.

Technology Capabilities

Gradiant capabilities rely on 3 different fields: Connectivity, Communications and Inteligence.

Gradiant develops technologies that enable seamless and secure connectivity across terrestrial and non-terrestrial networks. Its expertise includes 5G and 6G networks, satellite communications, IoT ecosystems, cloud-edge architectures, and the integration of next-generation communication infrastructures.

The organization designs advanced communication systems for complex and mission-critical environments. Its capabilities cover wireless communications, signal intelligence (SIGINT), spectrum monitoring and management, integrated sensing and communications (ISAC), broadcast and satellite systems, and secure communication technologies.

Gradiant leverages Artificial Intelligence and advanced data analytics to transform data into actionable insights. Its capabilities include machine learning, computer vision, multimedia analytics, natural language processing, intelligent automation, predictive analytics, and autonomous decision-support systems. These technologies are applied to improve operational efficiency, security, monitoring, and decision-making across multiple industries.

Main equipment or Facilities

General laboratory capabilities and infrastructure
Gradiant has an on-premises fully equipped quantum optics laboratory, for development, testing and characterisation of hardware for quantum sensing and quantum communications It also possesses optical benches to insulate from mechanical perturbations. The laboratory is capable of sustaining the ideal conditions to work with atomic-based technologies (Rydberg atoms, cold atoms), solid state technologies (diamond NV centres and other colour defects) and photonic-based technologies (integrated photonics).
Gradiant is equipped with an infrastructure, based on NVIDIA GPU clusters, specifically designed to facilitate the training and testing of Machine Learning algorithms. This infrastructure, owned by Gradiant, is hosted by CESGA, Galicia Supercomputing Technological Center. It has 2 nodes, both of them with 64 GB of RAM, 16 cores, and 32 threads, Node 1 with three Nvidia GPUs (GeForce RTX 2080 Ti, NVIDIA TITAN RTX, and GeForce RTX 3090), and Node 2 with four (2 x GeForce RTX 3090 and 2 x GeForce RTX 2080 Ti).

The 5G cybersecurity laboratory is designed to validate 5G network components, develop and validate new technologies, and assess cybersecurity in sector-specific applications and services that utilise 5G technology, such as Smart Transport. Furthermore, this laboratory focuses on identifying potential vulnerabilities and threats by conducting cybersecurity attack simulations and automating responses to them, thereby strengthening the network infrastructure. The laboratory utilises a range of advanced technologies to ensure the security, privacy and integrity of information on 5G networks.

The laboratory also uses Large Language Models (LLM) to simulate advanced attacks and automate penetration testing. Furthermore, these models facilitate the orchestration of incident response, the rapid analysis of security data and the creation of detailed reports on security incidents.

Contracts for Big Science facilities

No registered contracts

Relevant R&D projects

[Horizon Europe] SELF-SUSTAINED PHOTONIC SYSTEMS THROUGH AUTONOMOUS LOSS HARVESTING (BLOSSOM ) (2026)

The main objective of this project is to harness the parasitic energy (i.e., losses) of photonic integrated components and reuse it to drive the components themselves, enabling their operation with near zero external power requirements. This approach aims to revolutionize integrated photonics by drastically reducing energy consumption and enhancing sustainability. We propose collecting these energy losses using precisely designed Electro-Optical interfaces (transducers) and directing them to an integrated power management unit (PMU) that can store and release energy on demand back to the system. We plan to explore various types of harvesting interfaces, including electro-optical polymer-plasmonic joints, traditional PN junctions, and advanced approaches such as 2D materials based on graphene, as well as natural energy harvesting methods using synthetic photosystem complexes. These methods are expected to push the frontiers of interoperability between molecular physics, electronics, and integrated photonics. A key element of our vision is the creation of a photonic integrated neuron that is self-sustaining. This neuron would be part of a spiking machine where the parasitic energy collected and managed by the PMU triggers the system and enables the neuron to spike. This concept has the potential to pave the way for ultra-massive integrated photonic neural networks and neuromorphic solutions, where the size of the networks can scale exponentially without a significant increase in energy requirements.

[Horizon Europe] ETHICAL AND PRIVACY-PRESERVING BIG DATA PLATFORM FOR SUPPORTING CRIMINAL INVESTIGATIONS (PRESERVE ) (2024)

European project aimed at designing, implementing, and validating an advanced set of tools that will enable security authorities to collaborate more effectively and securely while ensuring citizens’ privacy. To achieve this, it will leverage Federated Learning technologies, which allow artificial intelligence models to be trained in a decentralized manner without the need to share data between different entities. Additionally, it will integrate User and Entity Behavior Analytics (UEBA) techniques to analyze activity patterns using artificial intelligence and machine learning, enhancing the detection of potential threats and anomalies. project partners will develop a comprehensive solution to address key public security challenges by efficiently and securely collecting and processing large volumes of data from multiple sources. PRESERVE will focus on preventing child sexual abuse and detecting and mitigating hate speech through trend analysis and real-time monitoring. It will also work on assessing radicalization risks and identifying extremist activity using advanced tools, as well as detecting drug trafficking through data correlation and crime pattern analysis.

[Horizon Europe] 5G NETWORK SLICING ENHANCEMENT USING AI TECHNIQUES (5G-SLAICE ) (2024)

The main objective of this proposal is to implement an AI/ML based system to manage the dynamic allocation of resources to different slices in the Core of a 5G network. This system will take actions in two different aspects: it will be the responsible of scaling up and down different User Plane Functions (UPFs) associated to a specific slice, and it will be the responsible of reallocating the physical resources of the infrastructure to the virtual slices depending on the level of saturation of the 5G network or a specific slice. The proposed system will integrate two different types of ML algorithms: 1) Incremental Learning (IL) based algorithm for streaming time series forecasting regarding both users and state of the network; and 2) a Reinforcement Learning (RL) agent to automatically and optimally manage the 5G network resources, considering current and future states. To this end, the outputs of the IL model will feed the RL agent.

[CDTI - Cervera] CICERO (CICERO ) (2023 - 2025)

This project was created with the mission of launching a strategic R&D&i program in cybersecurity, focused on technology transfer, and complemented by the generation and recruitment of research talent in cybersecurity. It is a network composed of 113 researchers, 17% of whom are PhDs, with experience in the field of security, distributed across 5 work centers located in Galicia, Castilla y León, Catalonia, Andalusia, and the Basque Country. Currently, CICERO members generate over 20.7 million euros in revenue from this Cervera technology. The project will focus on 4 technological areas: – A2 Challenges in Identification: Focused on threat intelligence (through the automated analysis of honeypot data and the generation of realistic traces within them) and the identification of cryptographic vulnerabilities and exploitable weaknesses through side-channel attacks. – A3 Challenges in Protection: Research will focus on multipart computation models with processing in the encrypted domain, as well as post-quantum cryptography; and technologies to improve access control in digital onboarding processes. -A4 Challenges in Detection: Focused on the development of a prototype for anomaly detection based on multi-agent systems, the investigation of mechanisms for the protection of generative AI, and the development of a virtual cybersecurity laboratory. – A5 Challenges in Response and Recovery: Focused on digital forensic analysis of images.

[CDTI - Cervera] OPEN-VERSO (OPEN-VERSO ) (2020 - 2022)

This project is related to innovations stemming from the “Internet of Things”, machine-type communications, Industry 4.0, virtual reality, etc., which will be largely driven by the capabilities of next-generation mobile communication networks. 5G and beyond 5G networks will provide the necessary improvements in network architecture, bandwidth, and latency for these advances to become a reality. To support a successful transition, the development and improvement of testbeds is key to optimizing the capabilities of 5G networks. Unlike previous generations, 5G is no longer a closed monolithic technology but is made up of a set of tools that work collectively. Artificial intelligence, network access virtualization, self-management mechanisms, software-defined networks, and the constant update of standards make the availability of a controlled, comprehensive test and development environment essential to understand how these networks function and predict new use cases. The OPENVERSO concept is designed precisely to allow the members of the consortium to strategically position themselves in the development of these aspects.

Big Science Area

Particle physics and accelerators

Technology Areas

Information and Communication Technologies