No overall picture
You know AI can transform your business, but no one really knows where the company stands, or where to begin.
Artificial intelligence consulting, from audit to automation: method first, processes next, technology last. Each pillar can be launched on its own or combined with the others.
You know AI can transform your business, but no one really knows where the company stands, or where to begin.
Each department tests its own tools, often outside any framework: budget spread thin, data exposed, no consolidated results.
Without priorities or indicators, it is impossible to prioritise, convince leadership or measure results.
Team skills, processes, data, and infrastructure & security: a score for each, compared with what is achievable for you.
We start from your reality, not from a generic questionnaire.
Which tools, used by whom, with what data and at what cost, including undeclared usage.
The most time-consuming, tedious or high-impact processes, assessed and ranked.
Confidentiality, GDPR and AI Act compliance, vendor dependency, access security.
Quick wins, priority projects, budget, expected gains and tracking indicators, presented to the leadership team.
Individual habits with no shared rules: results vary from person to person and nothing is captured or built on.
Without understanding how a model works or giving it the right context, you get generic output or errors. Trust collapses.
Without organised information or routines, AI adds to the chaos instead of reducing it. Tools are abandoned within weeks.
How a model reasons, context, hallucinations: understand in order to master, from leadership to teams.
Frame before you execute, one conversation per objective, never delegate clarity of thought.
A knowledge space structured by use, which the AI reads as permanent context.
Session wrap-up, weekly review, monthly clean-up: the system stays alive without effort.
Shared rules, best practices and a skills library that bring everyone to the same level.
Leadership, managers, teams: workshops on your own files. Also meets the AI Act's AI literacy obligation.
A few experts carry the methods: they cannot be delegated or improved, and the company is exposed when people leave.
AI is plugged into one-off tasks rather than complete workflows: the gains stay marginal.
A process that was never stabilised ends up breaking, costs maintenance, and the team disengages.
By frequency (daily, weekly, monthly, on trigger) and by function: acquisition, sales, delivery, support, administration.
Each process is scored on time spent, tedium and business impact. The most valuable go first.
Steps, quality criteria, examples, pitfalls: we capture what makes your way of working valuable.
Each method becomes a skill: a single process sheet the AI executes faithfully. Documentation and execution become one.
Manual, supervised, semi-automatic, then autonomous. Only on proven processes, with a named owner and alerts.
A shared skills library: every department benefits from the others' processes.
Emails, spreadsheets, ERP, CRM, documents: without a single source, AI consumes a lot, answers slowly and contradicts itself.
Who sends what, to which provider, kept for how long? Credentials and keys circulate outside any framework.
Spiralling costs, a single model, terms that change overnight.
A single source of truth for each piece of data, and connectors to your tools: ERP, CRM, office suites, document repositories.
Contractual Zero Data Retention (ZDR), European or sovereign hosting, local models for the most sensitive data.
Chosen by sensitivity and complexity, with no vendor lock-in. The model changes, your system stays.
Flat-rate plans rather than open-ended usage, budgets per use case, consumption tracking, tools enabled only when needed.
Secrets vault, least-privilege access, bounded permissions for agents, no exposed keys.
Tracking of usage, quality and costs. Your infrastructure adopts new models without starting over.