independent consulting · cloud data applications

Cloud data applications for mid-sized and large companies

Framing and taking on broad IT problems. Failures rarely occur inside a component: they occur at the interfaces. Between two clouds, two teams, two data regimes. Engagements are short, with a verifiable deliverable and a written handover, and run just as well with international teams.

The current passes, or it does not. The data and the compute are already there; what remains is the wiring, then the gesture. What closes can open again, and the previous position stays as a trace: the oldest image we have is a hand withdrawn from the rock. Against a climate shock, a health crisis or the acceleration of AI, resilience is not what you add, it is what you can cut without losing the rest.

01what is on offer

Six ways to engage, from scoping to production. Each produces a deliverable proven in the field, one an in-house engineer can read, take over and sign off.

build
web apps · analytics · machine learning
Web applications, analytics platforms and machine learning services, from prototype to production on AWS or Azure. Typical duration : 6 months to 1 year.
migrate and modernise
platform migration · legacy code
Cloud platform migration and legacy code takeover. Whatever must keep running through the transition, keeps running. Typical duration : 3 to 6 months.
audit and govern
system audit · data governance
Critical review of a system already in place; data governance set up so that it holds once the engagement ends. Typical duration : 3 months.
hand over and train
new platform · adoption · capability building
Adoption of a new platform by the people who will run it: the use case built with them, the architecture explained, training on their own data. The engagement ends not at the first dashboard but when the in-house team ships the next one unaided. Typical duration : 6 months to 1 year.
adopt AI and transform the trades
generative ai · agents · use cases
Adoption of generative AI and agents: use cases kept on measured impact, written rules of use, teams brought up to speed. What holds is not the model but the data, and the trades are what change, not the tool. Typical duration : 6 months to 1 year.
set up an online identity
association · liberal profession · independent
Identity and online presence for a small organisation: the deliverable is the system — tokens, components, written rules — not the pages alone, so the organisation carries on without its supplier. This site is the example.
A landscape in sepia ink and wash: a line of trees and low ruins, a cypress at the left, a great deal of paper above.
Claude LorrainRoman Landscape, mid-17th century
02recent engagements

Six real clients, sectors and roles.

2026AI agent strategy for the transport divisionUser support on generative AI, agents built on Copilot, tracking of vendor roadmaps.Egis Group2024Three Azure projects across the industrial businessSand detection in pipelines, refinery cost accounting, on-site risk assessment tool.TotalEnergies — Digital Factory2025HR use case and team training on Microsoft FabricImplementation of the use case, training the in-house teams on the chosen architecture.OCDE
03products

Open-source tools meant to make an independent’s life simpler. They belong to no client engagement: separate, open work whose assumptions are shown and editable. Two of them below, the rest on the products page.

open source · model · ai at work
DUTY

“It saves me time” comes apart into three claims: the work takes fewer hours, those hours are no longer alike, and more is expected of you per day. Six questions answered while reading, and the page works out which one is yours. What bounds the gain sits in the review, not in the speed of the model.

open source · simulator · wealth
FIRE

Long-term wealth drawdown, calibrated for France and Japan. Two tax regimes inside one model, which makes visible what the jurisdiction actually changes.

04latest writing

Positions taken from the engagements, dated to the day the work happened.

2026The grain of randomness: what decides a repetitionA generator of repeated fields is usually set with a single number, the quantity of randomness. It is the less decisive of the two. The one that decides the image is the level at which that randomness is injected, and it appears nowhere in the code.1 September 20262026Gale-Shapley at the milonga: stable does not mean fairThe algorithm behind the 2012 Nobel prize guarantees that no couple will walk off the floor together. It guarantees nobody a dance. Between those two promises the gap is wider than it looks.31 August 2026
A woodcut: geometric solids — an open torus, polyhedra, faceted slabs — set among ruined architecture, the whole rendered in hatching.
Lorenz StöerFantasy of Perspectival Forms Set among Ruins, 1567
05who you work with
Michel Hua
independent consultant · cloud data applications
2010Centrale Lille — Mechanical Engineering · Control Engineering · Applied Mathematics
2018MFG Labs, Havas Media Group
2023Artefact
based inParis · engagements in France and remote
technical stack
distributed computeAthena · Airflow · EMR · Databricks · BigQuery · Functions App · SQL Server · PostgreSQL · OpenAI · Claude · Snowflake · Bedrock · Fabric · Power BI
languagesPython · SQL · Java · Scala · Bash · Terraform
cloudAWS · Azure
certifications
Microsoft Certified Solutions ArchitectMicrosoft Certified AI EngineerMicrosoft Certified Data EngineerMicrosoft Certified Analytics EngineerGoogle Cloud Professional Cloud ArchitectGoogle Cloud Professional Data EngineerSnowflake SnowPro CoreHashiCorp Terraform AssociateGitHub ActionsGitHub Administration