Services - Generaition

AI consulting, auditing, ethics and governance

Many companies already use artificial intelligence solutions, but without full clarity on all the scenarios in which they need to ensure security, transparency or compliance.

We help you establish a foundation with clear rules, evaluating models and ensuring that AI always acts in a responsible and controlled manner.

What we do:

AI maturity diagnosis and associated risks.
Design of governance frameworks (roles, flows, validation).
Audits of models in production (bias, fairness, explainability).
Alignment with regulations such as AI Act, GDPR, ISO/IEC.
Support in decision-making with ethical impact (committees, evaluations, internal policies).

Data Engineering

Applying AI on disorganised or inaccessible data leads to errors, poor quality models and a huge waste of resources.

We help you prepare, govern and make your data accessible with clear structures and automated processes.

What we do:

Design and implementation of scalable ETL/ELT data pipelines.
Construction of cloud or hybrid architectures for storage, processing and efficient access to data (BigQuery, Databricks...).
Modelling and organisation of structured and unstructured data for advanced analytics and ML.
Implementation of data quality, cataloguing and data lineage systems (DataOps)
Orchestration and automation of processes with tools such as Airflow, dbt, etc.
Definition of governance models and access to data.

Customisation of AI models (education and training)

This service allows you to adapt generalist Artificial Intelligence models to the specific context of your organisation: your language, your data, your way of working… with your own data and specific structures.

Our goal is to train the models to deliver value from concrete use cases.

What we do:

Fine-tuning, RAG... of LLMs and other pre-trained models.
Creation of specific datasets for training.
Application of techniques such as prompt engineering or customised embeddings.
Evaluation of results with metrics adapted to the use case.
Design of retraining and continuous improvement workflows.
Generation of own embeddings for vector systems.

Creating AI solutions

This service is oriented to accompany organisations that detect processes that could be automated or improved with AI, but do not know how to move from the idea or business need to real and functional AI solutions.

What we do:

Identification and prioritisation of use cases with clear feedback.
Development of customised solutions: assistants, agents, recommenders, classifiers, etc.
Technical and functional validation of the solution in real environments.

Infrastructure, integrations and security

This service is designed to enable organisations to deploy AI solutions in secure, scalable environments that are connected to the existing technology ecosystem.

Often models work in testing, but fail to integrate or scale in real environments.

Our goal is to help you build a solid, well-connected and protected infrastructure where AI can operate without friction or risk.

What we do:

Audit and design of cloud-native or hybrid architectures for model deployment.
Deployment of APIs and containers (Docker, Kubernetes).
We develop and implement MCP Servers for models to run the necessary operations.
Integration with corporate systems (CRM, ERP, CMS, etc.).
Implementation of security, authentication, encryption and monitoring policies (IAM, Zero Trust).
Infrastructure automation (IaC with Terraform, CI/CD).
Security and compliance policies.

Optimisation and deployment

We ensure that models run in production with efficiency, speed and stability. We move from the lab to the real environment with a focus on performance and scalability.

Many organisations manage to train models, but encounter difficulties when trying to integrate them into their systems or implement them.

Our goal is to help you to ensure that these models do not remain in testing, but work in the day-to-day running of your operation.

What we do:

Conversion of models to optimised formats (ONNX, quantization).
Deployment as services (API, batch, edge computing).
Integration with inference pipelines and databases.
Automatic scaling according to load and demand.
Version management, rollback and maintenance.
Evaluation of costs and cloud efficiency.

Monitoring, analytics and visualisation

This service is designed to provide continuous monitoring and real visibility into the behaviour of AI models once they are in production.

Many AI projects work well at first, but over time they lose accuracy, introduce biases or fail undetected.

Our goal is to help you monitor what your AI is doing at all times, measure its impact and be able to react when something changes or stops working as it should.

What we do:

Performance monitoring and model (drift).
Automatic alerts for anomalies, errors or loss of accuracy.
Visualisation through dashboards for business and technology teams with metrics according to each of them.
Logging and full traceability of each inference or prediction.
Integration with existing observability platforms (graphana, kibana, etc.)
Visual audit on automatic decisions.

Innovation Lab and IA POCs

This service is designed to enable organisations to explore the potential of Artificial Intelligence without the need for large upfront investments, validating ideas in an agile and risk-controlled manner.

Often there are clear intuitions about where AI can add value, but the technical or business evidence to justify its implementation is lacking.

Our goal is to help you experiment meaningfully: turn hypotheses into working prototypes, evaluate their impact and decide with real data whether they are worth scaling up.

What we do:

Identification and prioritisation of use cases with AI potential.
Definition of the experiment: scope, success metrics and limitations.
Agile development of functional prototypes or proofs of concept.
Assessment of technical performance and business value.
Co-creation and knowledge transfer workshops.
Accompanying the transition from PoC to production solution (where applicable).
Support in the construction of the business case.

Synthetic Data

This service makes it possible to generate high quality synthetic data when real data are scarce, sensitive or directly inaccessible.

Many AI models cannot be trained properly due to lack of data or legal restrictions related to privacy.

Our goal is to help you create artificial but realistic datasets that allow you to train, validate or test models without compromising confidentiality.

What we do:

Suitable for synthetics.
Generation of artificial datasets (tabular, text, image) with validated fidelity.
Statistical and functional validation of the data generated.
Training and testing of models using synthetic data.
Regulatory compliance assurance (anonymisation, differential privacy, etc.).
Integration into existing AI pipelines or MLOps.

SEO AI Friendly

This service, in collaboration with a specialised partner, is designed to adapt the digital positioning strategy of companies to a new scenario in which search engines no longer work only with keywords, but interpret content with techniques similar to language models.

Our goal is to help you create and structure content that is understood by both search engines and generative models, so that your brand remains relevant.

What we do:

SEO audit with IA approach: technical, semantic and content structure analysis.
Restructuring of web content to facilitate its interpretation by LLM models.
Optimised content strategies for featured snippets and search by intent.
Integration of automatic content generation with AI under editorial control.
Continuous positioning, performance and adjustment monitoring.