Fasfox
About

Field experience meets technology

Fasfox grew from the meeting of hands-on operational experience and engineering. That dual heritage still guides our decisions, our work and our commitments.

A company that began with a real problem

Fasfox began on Grand Paris Express construction sites. While leading major projects, Vincent Raynal saw how poorly adapted tools made it harder to coordinate companies, monitor operations and share information.
He joined forces with Lélio Renard Lavaud, a software engineer and AI specialist. Together they created Suite Dispatch, a suite of tools designed around the way construction sites actually operate. That first venture established the foundations of the Fasfox approach.
Since 2018, Fasfox has applied the same way of working to industry, telecommunications, healthcare, public services and other demanding fields. Every project begins with a close look at the work itself and the constraints faced by the teams.

Complementary founders, directly involved in the work

VR

Vincent Raynal

Co-founder · Operations
École Polytechnique · Construction and civil engineering

A former Grand Paris Express project leader, Vincent brings a practical understanding of organizations, responsibilities and delivery constraints. He recognizes the difference between a process that looks elegant on paper and a system capable of working in the field.

You only understand a process by watching someone run it.
LR

Lélio Renard Lavaud

Co-founder · Technology
École Polytechnique · Telecommunications

A specialist in large-scale AI systems and Director of Engineering at Mistral AI, Lélio brings technical judgment formed at the forefront of advanced models, architectures and infrastructure.

Sophistication matters only when it makes the solution more appropriate.

What this combination changes for our clients

The brief is challenged

We do not mechanically validate the first request. We return to the problem and take responsibility for trade-offs.

Technical decisions stay rigorous

Architecture, data and AI choices are made by people able to understand their consequences.

Advice does not end at delivery

The same team remains accountable for coherence between the initial decision and the system in use.

Four principles visible in the way we work

Field reality first

No solution is designed until the actual work, constraints and data are understood.

Through to adoption

We remain involved after production until the new practice has found its place.

Partner, not supplier

We are transparent about progress and say clearly when an idea should be dropped.

Utility before fashion

We use AI when it creates genuine leverage, and a simpler system when it performs better.

A focused team around the project

Software engineers, AI specialists, product profiles and business experts work together. There is no advisory team handing the subject to a delivery team: those who frame the decisions remain involved in what gets built.

  • Senior involvement in key decisions
  • Short cycles and regular demonstrations
  • Direct communication with your teams
  • Production-grade quality