Transform your business processes with custom AI solutions
AI and data only create value when they address concrete business challenges. That’s why we design custom AI solutions, integrated into your tools and processes, to automate, improve reliability and enhance operational performance — without unnecessary complexity or fleeting trends.
Use-case driven AI expertise
We work on concrete data and AI projects, designed to meet specific business needs. Our approach prioritises utility, understanding of existing processes and integration of solutions that are genuinely usable in your environment.
Data science & Machine Learning
Design of statistical and machine learning models to automate or enhance business decisions, through reliable, interpretable models adapted to operational constraints.
Generative AI & LLM
Implementation of solutions based on language models for content analysis, search, summarisation, translation or assistance, with fine-tuned adaptation to business use cases.
Intelligent search
Development of intelligent search and similarity engines combining data, machine learning and generative AI to identify, compare or qualify content at scale.
Hybrid AI architectures
Design of architectures combining classical models, generative AI and specialised agents, using each technology where it delivers real value, without over-automation.
/ A pragmatic and iterative approach
We favour a progressive approach, centred on business understanding, rapid validation and controlled industrialisation, to secure results and solution adoption.
Business scoping
Immersion in your processes, identification of business challenges, key criteria and technical constraints to establish a clear, shared framework.
Prototyping
Building first prototypes and targeted tests to validate hypotheses, compare approaches and adjust technical choices.
Iterations
Progressive improvement of models and rules based on feedback, with regular demonstrations and business validations.
Industrialisation
Development of orchestration, automation of processing and performance hardening for reliable, repeatable use.
Deployment
Production deployment and integration into your tools and processes, with performance monitoring and adjustments as needed.
/ AI ecosystem
We select technologies and models based on your use cases, constraints and stability requirements. Our approach favours complementarity of tools and adaptation to your existing environment, without dependency on a single solution.
AI architectures designed for stability, integration and business value.
/ They leverage their data with Castelis
Discover how our clients have turned their data into levers of performance and operational decision-making.
SNCF | Optimising the fine recovery rate
Machine learning applied to fine recovery to optimise targeting and reduce processing costs.
Solocal | Feeding a data hub from external IS
Multi-IS data centralisation middleware to accelerate client onboarding on the Bridge platform.
Groupe Qualiconsult | Accelerating payment allocation
AI and OCR tool to automate accounting reconciliations and reduce payment allocation lead times.
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Frequently asked questions — Custom AI
No, and that’s precisely why our approach starts with the business. We assess the real relevance of AI based on your processes, data and objectives. In some cases, simpler approaches can be more effective and more sustainable.
No. We combine data, classical machine learning and generative AI depending on the needs. Each technology is used where it delivers measurable value, without over-automation or unnecessary dependency.
Yes. Our solutions are designed to integrate with your existing tools and applications to ensure adoption and operational use, without disruption for teams.
Through an iterative approach, regular business validations and robust architectures. We prioritise model stability, processing traceability and performance monitoring over time.
Yes. Solutions are designed to evolve progressively, based on new requirements, new data or changes in your usage, without disrupting what is already in place.
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