The AI Studio turns your strategy into tools.
Most of our missions end with a solid plan — and one question: who will keep it running day to day? The AI Studio answers by building the tools the teams are missing: better processes run on better tools, better built and better integrated.
Let’s talkBorn on missions. Built to serve.
The bespoke tool your teams always wished for exists, and we build it in two to three months. The days of choosing between off-the-shelf software you must bend to and development you cannot afford are over.
What changed is not the cost of code — it is what you can finally attempt. A process that fitted no software. Know-how living in three heads. A decision waiting for the right spreadsheet.
Those who seize it learn and decide faster, and turn know-how into an asset. The others will go on buying presentations, and will fall behind without noticing when.
The hard part is not building the tool. It is choosing which one.
Four steps, held by a small team and powered by AI. The first two set the strategy. The next two go through our AI Studio, which builds the bespoke tools.
Interviews with executives, teams and the market; company data; benchmarks. Our agents read the whole corpus, not a sample.
The four or five subjects that make the value.
The trajectory, quantified, written with the executive committee: initiatives, owners, milestones, indicators. One document fit for the board, the investors and the teams.
A trajectory everyone can read.
The AI Studio builds the tools that move the plan forward, on your data and inside your processes: what took three days takes one. Alongside it, monthly review, decisions, subjects taken back in hand.
Tools in service, a plan that moves.
The tools built during the mission stay in service, your teams run them, the governance works without us.
An autonomous team, tools in service.
This is the forward deployed model — Palantir’s, adopted by the AI labs: no specification document, we embed with you and ship code that runs on your data.
Interviews and a workshop with the people who do the work. We pick one use case on value and feasibility, we look at the real state of your data — the thing that derails AI projects — and we write the evaluation set: the cases the tool will have to get right.
Continuous development, not a prototype: a version runs on your data from the first week, in the hands of ten users, corrected with them every week and measured against the evaluation set. Three weeks for a team assistant; longer as soon as the domain is regulated or the data is messy.
Authentication, permissions, security, data migration, acceptance. Two to four weeks depending on your information system, set with your CIO once the tool is built.
Train the teams, measure real usage and the effect on the numbers, fix what sticks, re-evaluate when the models change — they change every quarter — and extend to the next perimeter. Your teams take over whenever they decide.
Five tools born on missions, with funds and with companies. Each one can stay with its client and keep running: it is often the best way to make the impact of the mission last.
Born with Argos Wityu
AI steering for a portfolio — Monitor. Value. Decide. Your data, Excel or ERP, becomes one reconciled screen: fund and company performance, value creation plans, simulated exit scenarios, agents that answer in natural language. One source of truth, instead of the spreadsheet that keeps cracking.
Born with Aconic Avocats
The legal AI that has references. Skills for the firm’s own moves, MCP connectors into more than a hundred official corpora — Légifrance, Judilibre, EUR-Lex, INPI, CNIL — and agents that search, draft and check, installed inside the assistant the lawyers already use. Every fact traces back to its source; queries never leave the firm.
Born with Siparex
Large-deal diligence, in mid-cap format: double materiality by ESRS, a 0–4 maturity score argued line by line, a peer benchmark, priorities with KPIs. Tooled, it fits in four days — and the tool does not replace the interviews, it prepares and cross-checks them.
Born with Santé Cie
Coordinating every actor of home care around the patient: private nurse, doctor, pharmacist, care provider. From problem to code — design thinking workshops, carers’ pain points, target features actor by actor, prioritised user stories, architecture. Initial perimeter: nursing coordination in oncology, the most demanding journey of all.
Born with Demeco · Hexvia group
A network where every salesperson ran the video visit their own way. The sales process written like a play — four acts, five scenes for the video visit — the memo to keep in sight, the sketches acted out as a team, a named coach. Then AI in the loop: what the best ones do, fed back to everyone else. The video visit is now standard across the group.
Authentication, permissions and isolation are decided with your CIO on day one, not at acceptance testing. Source code auditable end to end, tracked dependencies, a security review before go-live.
Data minimisation from the outset, anonymisation where it suffices, access logging. GDPR, health data, professional confidentiality: the framework decides the architecture, it is not bolted on at the end.
Local demo — cut the network and the application still works. Production inside your perimeter, with your authentication. Self-hosted model when you ask for it, chosen with your CIO.
AI writes the code, it does not see your data. What you entrust to us trains no model and goes into no tool sold to anyone else. You will find no client figures anywhere on this site, either.
Tell us the task that costs you the most: the one your teams redo every week, the one that hangs on a single person, the one still waiting for the right file. We come back with the tool to build, and its roadmap.