Four ways to work together.
Start with what is holding you back. Each service stands on its own, and they fit together.
Build
From idea to a working product, live and in use.
For founders who need to launch, and for teams who need a tool the market doesn't offer.
What you get
- An MVP or SaaS ready for its first users
- A custom business platform or back office
- A client portal with accounts, roles and documents
- A dashboard wired to your real data
The whole chain, no hand-offs
- UX/UI
- Frontend
- Backend
- Database
- Authentication
- API
- Deployment
It's for you if
- The idea is clear but nobody in-house can build it
- You want a live product before hiring a full team
- Off-the-shelf software forces you to work around your own process
Examples: SaaS MVP with AI, client portal, custom back office.
Automate
Your tools finally talk to each other. Repetitive tasks disappear.
For SMEs and agencies whose days go on data entry, chasing and copy-paste.
- Form
- Supabase
- n8n
- AI
- CRM
- Email, Slack
- Reporting
What you get
- Workflows that run on their own, with a log of every run
- Integrations and syncs between your existing tools
- Useful notifications, sent to the right person
- A CRM that fills itself without re-keying
How
n8n to orchestrate, REST APIs and webhooks to connect, Supabase as the single source of truth. I connect what you already have rather than replacing everything.
It's for you if
- The same manual task comes back every day or every week
- Your data lives in Excel, email, WhatsApp and a half-filled CRM
- A re-keying error has already cost you a client or an invoice
Examples: invoice reminders, request qualification, connected dashboard.
AI
AI where it saves time or improves a decision. Nowhere else.
For teams who want to use AI but don't yet have a concrete use case.
What you get
- Assistants and agents connected to your data and your tools
- Automatic analysis of documents, emails or requests
- Content generation governed by your rules
- Qualification and sorting of whatever comes in
Four questions before adding AI
- Is the gain measurable? Time saved, fewer errors, a better decision. If not, we don't do it.
- Does the cost per use hold up? Every call has a price. It must stay small next to what it saves.
- What happens when it gets it wrong? AI makes mistakes. The system has to anticipate them and catch them.
- Who approves sensitive decisions? A human, always, when the stakes call for it.
Examples: qualification agent, SaaS with AI at its core.
Product System
Interface, data, automations and AI designed together, in a single system.
For projects where the problem cuts across several layers: the most common case, and the most profitable.
Why design it all together
When the interface, the database, the workflows and the AI are designed by the same person, there are no gaps between the layers and no meetings to work out who owes what to whom. The system is coherent from day one, and it evolves as a single whole.
Examples: client portal, CRM with qualification, this website.
How it starts.
- You describe the problem.What is costing you time, money or quality. No specification document needed.
- We scope it together.Scope, deliverables and how success will be measured, in writing, before the first line of code.
- I build, you see it.A prototype first, then regular demos all the way to go-live.