Data, automation and AI for SMEs
Reliable data. Simpler processes. IA that actually works.
I help SMEs and service organisations move beyond fragile files, manual reports and copy-paste-heavy processes. The goal: make what matters reliable, automate what slows you down, and use AI only where it adds real value.
field scoping
From reliable signal to useful workflow
Before AI, there is often a simpler problem
Many AI projects stall for very concrete reasons: incomplete data, implicit business rules, tools that do not talk to each other, checks done too late. You often gain more by fixing those foundations than by adding yet another tool.
- Excel files that have become too sensitive to stay patched together
- Reports rebuilt by hand every week or every month
- CRM or data migrations where checks arrive too late
- Tasks copy-pasted between forms, emails, CRM and spreadsheets
- AI ideas circulating, but with no clear priority or scope
- Decisions made with data that still needs to be verified
Three ways to start without over-engineering the project
The right entry point rarely depends on the technology. It depends on what wastes your time, what causes errors, and what your teams will genuinely be able to adopt.
AI & automation diagnostic
Sorting the good ideas from the gadgets and the topics that need preparation before launching a project.
- processes to automate
- available data
- risks and prerequisites
- short-term action plan
Data quality, reporting & testing
Putting controls where errors are costly: migrations, data flows, dashboards, business rules.
- SQL tests
- source / target reconciliation
- consistency checks
- more reliable reporting
Automations & business tools
Building workflows, AI assistants or small applications that remove manual work instead of adding another tool.
- n8n workflows
- business assistants
- simple portals
- operational tracking tools
We clarify before we build
A useful project often starts with simple questions. Which data is reliable? Which tasks really repeat? Which business rules need to be made explicit? And above all: what is actually worth building right now?
- What needs to be made reliable before talking about AI
- What can be automated without rebuilding your entire system
- What deserves a prototype rather than a large project
- What your teams will need to understand to actually use it
A short method, grounded in reality
No lengthy project tunnel: we start from the field, make decisions, test, and adjust.
Assess the terrain
We start from your tools, your files, your business rules and the places where work genuinely gets stuck.
Filter the ideas
Not every AI idea deserves a project. We keep those that can help quickly without complicating day-to-day work.
Build small
We put a control, an automation, an assistant or a business tool in place on a clearly defined scope.
Drive adoption
We document, train and adjust after the first uses. A useful solution must actually be used.
Why work with Adygital?
My experience comes from projects where data errors, CRM migrations, acceptance testing and reporting are not abstract topics. They are very concrete blockers, with real impact on teams, decisions and clients.
- Over 15 years of experience in data, CRM, software quality and IT transformation
- A culture of SQL, testing and reliability forged on demanding projects
- The ability to scope the need, then prototype or implement a concrete solution
Blog
First reference points for scoping your data, automation and AI projects
Short articles to prepare the right topics before launching a tool or a development.
Pourquoi les PME ne doivent pas commencer l’IA par un chatbot
6 juin 2026
Le chatbot est souvent le premier réflexe quand une PME veut tester l’IA. C’est rarement le meilleur point de départ si le processus, les données et les règles métier ne sont pas encore clairs.
Read articleAgent IA, automatisation ou application métier : comment choisir ?
6 juin 2026
Le bon format dépend du travail à améliorer. Un agent IA, un workflow automatisé et une application métier ne répondent pas au même besoin, même s’ils peuvent parfois se combiner.
Read articleAvant de lancer un projet IA, regardez vos données
6 juin 2026
Un projet IA utile commence rarement par le choix d’un outil. Il commence par une lecture claire des données, des règles métier et des usages réels.
Read articleContact
Parlons de votre projet
Vous avez une idée d’automatisation, un besoin data ou une question sur l’IA ? Écrivez-moi quelques lignes.
Un échange concret pour clarifier vos besoins, vos priorités et les prochaines actions utiles.