Our approach
Most AI projects fail because they are designed as isolated experiments, not as solutions integrated into the business. We start with the real problem, measure impact from day one and deliver systems your team can use and maintain.
Talk to an expertEvery AI project we take on starts from a use case with measurable impact: reduced operational costs, higher conversion, improved quality or accelerated processes. We do not run pilots for the sake of running pilots.
The AI we develop connects with your existing ERP, CRM, database or digital platform. We do not replace your technology stack — we make it smarter without friction or costly migrations.
We build explainable and auditable AI systems. Your team understands why the AI makes each decision, can correct errors and retains control over critical business processes.
Solutions we develop
We identify high-volume repetitive tasks and automate them with AI: document classification, data extraction, form validation, request routing and much more.
We build machine learning models to forecast demand, detect anomalies, segment customers, anticipate churn and optimise prices or inventory using your historical business data.
We develop conversational assistants powered by LLMs (GPT-4, Claude, Llama) trained with your company's context: customer support, internal help, report generation and semantic search.
We turn knowledge bases, contracts, manuals and emails into assets you can query in natural language using RAG (Retrieval Augmented Generation) and vector embeddings.
We design autonomous agents that chain complex tasks: receive a goal, query external systems, make intermediate decisions and deliver results without constant human intervention.
Detection, classification and visual recognition systems for industrial quality control, perimeter security, automatic document reading and real-time image analysis.
Our methodology
We analyse your processes and available data to identify where AI can generate the most value. We define the use case, the target KPI, the required data and technical feasibility before writing a single line of code.
We carry out an exploratory analysis of available data, assess quality and volume, and design the technical architecture: models to use, required infrastructure and integration with existing systems.
We develop, train and validate the AI model or system using real data from your company. We iterate on results with objective metrics until production-ready performance is reached.
We integrate the AI solution into your existing workflows and systems via APIs or direct connectors. We deploy on the most appropriate infrastructure (cloud, on-premise or hybrid) with monitoring from day one.
AI models degrade over time without maintenance. We set up retraining pipelines, monitor production performance and evolve the solution as your business and data change.
Technical capabilities
We combine the most advanced AI techniques and tools with a pragmatic approach: we choose the right technology for each problem, not the trendiest one.
Integration and fine-tuning of large language models such as GPT-4, Claude or Llama for conversational use cases, content generation and text analysis at scale.
Text classification, sentiment analysis, entity extraction, automatic summarisation and translation applied to emails, contracts, reviews and internal documents.
Retrieval Augmented Generation systems that allow LLMs to answer accurately using your company's proprietary knowledge stored in vector databases.
Supervised and unsupervised models for demand forecasting, fraud detection, churn, lead scoring and any classification or regression problem with tabular data.
We implement explainability techniques (SHAP, LIME) so models are auditable, comply with regulations such as the EU AI Act and build trust among users.
We connect AI solutions with your ERP, CRM, databases, cloud platforms and any internal system via REST APIs, webhooks or direct connectors.
Object detection, image classification and intelligent OCR models for quality control, document recognition and automated visual analysis.
Training pipelines, model versioning, production monitoring and automatic retraining to ensure your AI systems operate reliably in the long term.
Featured projects