Velours Automation
Your processes, without the data entry.
We design and run custom automations built on the best frontier models available. Every project starts from a real process, measured before and after.
What a well-scoped automation produces, with the right model behind it.
- Weekly tender monitoring
- 6 h → 20 minWeekly tender monitoring
- Invoices cleared untouched
- 92%Invoices cleared untouched
- Tickets closed at first line
- 61%Tickets closed at first line
- From scoping to production
- 3 weeksFrom scoping to production
Method
Four steps, no grey areas.
A narrow scope, shipped fast, then extended. We pick the model case by case, and you keep control of the code and the credentials.
- 01
Scope
Two days on your process. We measure the time it takes, find what repeats, and work out what a model can handle today.
- 02
Prototype
A first version in production on a narrow scope, within two weeks. Candidate models are benchmarked on your own data.
- 03
Ship
Edge cases handled, monitoring and alerts in place. Your team is trained on it.
- 04
Run
We watch it, keep it current, and move to a better model as soon as one ships. Or you take over, the repository is yours.
Use cases
Three processes we have automated.
Each one lays out the full workflow, the models chosen and the stack behind it.
- Public procurement
Tender monitoring and response
Catch relevant notices on BOAMP and TED, qualify them with frontier language models, and assemble the response pack.
6 h → 20 minWeekly monitoring3xQualified opportunities - Finance
Supplier invoice processing
Read invoices from a shared inbox with a multimodal model, check them against purchase orders, and prepare the ledger entries.
92%Invoices cleared untouched4 d → 1 dApproval time - Support
First-line support triage
Classify incoming requests, answer what is already documented through LLM-backed retrieval, and route the rest to the right team.
61%Tickets closed at first line8 minFirst response
Principles
How we work.
The best models available
Claude, GPT, Gemini, Mistral. We stay provider-independent and run whichever wins on your task, measured on your data.
The code is yours
Git repository, hosted on your side if you prefer. No dependency on our infrastructure.
Data stays in Europe
European hosting by default. Self-hosting available for sensitive data.
Humans decide
The model prepares, sorts and proposes. Calls that commit you stay yours.
Measured both ways
We put a number on the time spent during scoping, then measure it again. Every model is scored against a test set built from your real cases. No gain, no next phase.
Your existing tools
We connect what you already use instead of adding another tool. The AI slots into the process you have. No migration first.
Built to hand over
Documentation and handover planned from the start. Your team can take it from us.
Frequently asked
- How long before something runs in production?
- Two to three weeks for a first scope. Scoping takes two days, the prototype follows.
- Which models do you use?
- Frontier models: Claude, GPT, Gemini, Mistral, depending on the task. We are tied to no provider. The choice is made against a test set built from your real cases, and revisited whenever a better model ships.
- What happens when the automation gets it wrong?
- Every step logs what it did, model calls included. Uncertain cases go to human review instead of being guessed. You can see what happened and why.
- Where is our data hosted?
- In Europe by default. Models run under enterprise terms, with no reuse of your data for training. For sensitive data we install the whole chain on your own infrastructure, with an open-weight model running locally if needed.
- Are we locked in afterwards?
- No. The code sits in your repository and the documentation ships with it. We offer a monthly retainer with no minimum term.
- Do you work with n8n?
- Yes, where it fits. For more demanding chains, or as soon as several models need orchestrating, we write code and deploy it on your side. That choice is made during scoping.
Got a process in mind?
Describe it in two lines. We will tell you whether today's models can handle it, and what it would take.