A look at our work: industry, services, retail, software publishing — technology stacks chosen to fit the context, and engagements ranging from diagnostics and training through to enterprise AI platforms. Each case is described by what allows comparison: the sector, the size of the organisation, the engagement, the technologies used and, where measured, the gain.
17 references shown
Deployment of the infrastructure, connection of existing applications and creation of a generative AI tool for tenders based on historical data, CVs and regulations, with dedicated support.
Set-up of an internal AI platform enabling employees to use secure models, create personalised assistants, capitalise on company knowledge and automate document search and translation, replacing existing solutions.
Roll-out of the first conversational agents allowing business teams to query their data in natural language, speed up access to key information and ease day-to-day decision-making.
Development of a decision-support assistant connected to the company’s data, allowing executives and business teams to query indicators in natural language and instantly obtain actionable analyses, summaries and reports.
Exhaustive reverse-documentation of data flows to produce a complete map of the information system. Improved readability that enables targeted interventions, dependency control and easier maintenance for teams.
Dependency control and easier maintenance
Automatic AI classification of 14,000 suppliers according to a bespoke taxonomy. Structuring and standardising spend data to feed reliable analytical dashboards and optimise procurement management.
70+ days of research and data entry saved
Development of 8 boosters designed to speed up scoping phases, reduce analysis effort and make designs more reliable.
120+ days of traditional analysis saved
AI analysis of input and output data: detection of grey areas in the specifications and co-drafting of technical specifications. An approach that speeds up the design phase and secures deadlines.
Shorter design timelines
AI-automated reverse-documentation of existing flows, followed by automatic generation of bespoke technical specifications. An approach that speeds up the transition while ensuring compliance with internal standards.
Standardisation and cost reduction, ~90 days
Development of an AI-enhanced business application enabling CVs to be created, updated and queried in natural language, to improve skills management, access to information and teams’ operational efficiency.
Implementation of a solution dedicated to the continuous improvement of data quality, combining control, enrichment, consolidation and deduplication, to ensure consistent and usable information.
Development of a FinOps Cloud & AI steering module offering a consolidated view of costs, consumption tracking, drift detection, budget optimisation and carbon footprint analysis.
Data sovereignty and cost control
Facilitation of an AI-awareness workshop during a company seminar: hands-on training in internal tools and practical work on concrete business cases, to encourage immediate, operational buy-in.
Facilitation of a conference and workshops confronting preconceptions with the actual figures. Objectives: understand how AI works and provide the practical and strategic keys to adopting it effectively while avoiding common pitfalls.
Roll-out of a complete programme: employee AI awareness, structured upskilling and accelerated adoption of new uses through the introduction of AI passports.
Audit of the existing set-up and operational recommendations to improve the scheduling of interventions, field performance and decision-makers’ decision-making, illustrated through a technology POC.
Facilitation of an AI-awareness seminar aimed at understanding its opportunities, assessing the organisation’s maturity, identifying concrete use cases and engaging teams in a pragmatic transformation process.
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We can share the context, the approach and the pitfalls encountered — subject to the client’s agreement.
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