Consulting

Business and Technology Consulting

Drive digital transformation with Neurosymbolic AI

The consultancy service analyses and studies the specific needs of each organisation to design tailored technological solutions, taking into account both the project requirements and its economic and time constraints. The GNOSS team advises, guides and provides support on technological aspects and challenges that an organisation cannot resolve internally.

• Comprehensive assessment of business needs and current technical capabilities
• Design of Neurosymbolic AI-based architectures to address specific challenges
• Development of roadmaps for progressive implementation
• Support in strategic technology decision-making
• Measurement of results and impact on business objectives

The technology consultancy approach is grounded in a deep understanding of business challenges, translating them into personalised, efficient Neurosymbolic AI solutions oriented towards concrete results.

Ontological Engineering

Build the artificial mind of your organisation

This area specialises in the design of ontological models for the semantic representation of data in digital ecosystems. The approach involves analysing existing ontologies, reference conceptual models, vocabularies and metadata schemas to propose a bespoke ontology network for each project, taking into account both the intended uses and the human factors that will determine user-machine interaction.

With the aim of accelerating the development of different ontologies and improving project management, the team formalises and provides precise methodological guidelines that steer software engineers and ontology specialists, offering the technical and knowledge support needed to ensure successful outcomes.

• Specification of ontological requirements.
• Planning and support for ontology development.
• Reuse of domain ontologies and ontological hybridisation.
• Reuse of ontological design patterns.
• Ontological modelling.
• Development of operable ontologies.
• Management of ontology evolution and versioning.
• Support for multilingual ontologies.
• Comprehensive documentation and summaries of ontological models.
• Generation of linked data systems for information enrichment.
• Design and development of idea or concept ontologies linked to specific areas of knowledge.

The area consolidates its knowledge in a well-documented ontology knowledge base — which can be offered as a service in its own right — and documents methodologies for building semantic applications, with particular emphasis on the creation of applications that use linked data.

The mission is to provide the guidelines and technologies for the development, management and efficient use of ontological networks, accelerating development and improving the quality of semantic models across every GNOSS project.

DATA

Consolidate heterogeneous, distributed data silos into a single digital ecosystem

The DATA area handles the detailed analysis of the data sources and information systems that must feed the knowledge graph — or "mind" — of the system:

• Identification of the nature, degree of structuring and normalisation, update frequency, format and availability.
• Identification, design and construction of APIs or data collection systems.
• Design and implementation of ETL processes for data extraction, transformation and loading, providing the essential foundation for data to be consumed coherently by a knowledge graph, an analytics system or machine and deep learning processes.
• Synchronisation, semantic annotation and knowledge graph population processes.
• Dynamic update methods for consolidated data.
• Identification and configuration of Big Data technologies where required.

Human Factors Engineering

Ensuring cognitive ergonomics in human-machine interaction

The Human Factors area is concerned with making the relationship between people and machines cognitively ergonomic and meaningful. It covers all work related to the design and definition of interaction processes with information systems, ensuring the best possible user experience through usable, effective and intuitive interfaces.

• HOI (Human Ontology Interaction) services
• HCI-HCIR (Human Computer Interaction – Human Computer Information Retrieval) services
• UX (User Experience / Information Architecture in IT systems) services
• Interface and digital experience design
• Dialogue flow design for conversational assistants
• Graphic identity and design system development

The goal is to optimise people's wellbeing in their interactions with intelligent IT systems, placing users at the centre of design and development processes and applying theory, principles and methods across all components.

Human-Ontology Interaction and Human-Computer Interaction (HOI-HCI)

Integrate and uncover the hidden knowledge in your data

This service focuses on the conceptualisation, design and construction of querying, context generation, profiling and recommendation systems that exploit the knowledge graph based on the knowledge objects defined in each project.

• Semantic querying interface design
• Dynamic context generation systems
• High-precision user profiling engines
• Entity and relationship-based recommenders
• Interactive knowledge graph visualisations

The approach ensures that users can interact with complex systems in a natural and intuitive way, maximising the value extracted from the underlying knowledge graphs.

Cognitive and AI Services and Automated Reasoning Services

Give your systems cognitive capabilities

The team designs and builds algorithms and processes that apply heuristic methods using machine learning and deep learning, language processing technologies and large language models (LLMs). These technologies are used to improve knowledge metadata, interpret it, extend it and enrich it with external sources, designing services that replicate some of the capabilities of human cognitive function.

The European Commission defines AI as human-designed software and hardware systems that, when faced with a complex objective, act in the physical or digital dimension. Following this definition, GNOSS systems operate across three fundamental dimensions.

• Perceiving their environment, through the acquisition and interpretation of structured and unstructured data.
• Reasoning over knowledge, processing the information derived from this data and deciding the best actions to achieve defined objectives.
• Learning from data systems, linking information and discovering relevant patterns.

GNOSS is committed to developing trustworthy, traceable and explainable AI systems — which in practice means hybridising knowledge graphs with cognitive and AI services. This combination ensures that systems can interpret the world, reason about it and learn contextually. Knowledge graphs provide AI with the traceability conditions necessary for it to genuinely meet these requirements.

The goal is to create systems that augment people's cognitive capabilities and can carry out tasks that normally require human intelligence — such as learning, reasoning and perception — always keeping the human being at the centre of the process.

GNOSS's full suite of Cognitive, AI and Automated Reasoning Services is consolidated in GNOSS Cognitive Services and AI Platform.

• Construction of general-purpose and project-specific knowledge bases
• Integration of NLP-NLU services focused on unambiguous entity extraction and disambiguation
• Incorporation of generative technologies and LLMs aimed at humanising the relationship between knowledge graphs and people
• Design of open-world generative conversational assistants
• Development of inference engines and automated reasoning systems based on inference

This Neurosymbolic AI architecture makes it possible to create solutions that do not merely generate responses, but genuinely understand the context and meaning of the information they work with, delivering auditable, verifiable and traceable results.

Content and Training

The area handles the construction of training datasets and the human supervision processes of learning systems, as well as the curation, classification, annotation and semantic representation work carried out with expert information specialists.

• Generation of training datasets with precise labelling
• Improvement of annotation criteria to reduce the subjective nature of interpretation
• Supervision of training results and generation of retraining datasets
• Consolidation of automatic information categorisation systems, supplementing their limitations with human capabilities
• DATA and content writing services in GNOSS projects

The team guarantees the quality of training data and expert supervision of learning systems, ensuring the highest possible accuracy in every AI project.

Semantic Systems Development and Engineering

Build Neurosymbolic AI solutions operable by machines

The area handles the development of Neurosymbolic AI solutions tailored to the needs of each organisation, hybridising GNOSS Semantic AI Platform with Cognitive Services and AI Platform, building user interfaces and configuring both platforms across all their dimensions — both ontological and user experience.

• Implementation of information retrieval and exploration systems
• Development of semantically enriched record pages
• Construction of profiling and recommendation systems
• Publication of knowledge graph services and views for machines and people
• Ensuring usability, accessibility and SEO across all applications

The consultancy team combines advanced technical knowledge with strategic vision to deliver solutions that respond to specific business needs. Work is carried out in close collaboration with each team throughout the entire process, ensuring that the solutions developed align perfectly with the established objectives.

With a Neurosymbolic AI-based approach, GNOSS transforms the way organisations manage, interpret and use data, making it possible to uncover new opportunities and optimise processes with a clear return on investment.