What we do, and what you keep.
01
Decide
Strategic support for leadership teams
- Who it’s for
- Executive teams and CIOs.
- The problem
- Structural choices (models, vendors, hosting, architecture) to make fast, in a market that changes every month.
- What we do
- Support on your AI choices: strategy, architecture, stack, trade-offs.
- What you keep
- Reasoned, written choices you can defend without us.
02
Train
- Who it’s for
- From leadership to technical teams.
- The problem
- Very different levels within one organization, and generic training that changes nothing day to day.
- What we do
- Training on our specialties: Skills, context, agents (Claude, Claude Code and Hermes in particular) and strategic monitoring. Live demos, on your own cases.
- What you keep
- The materials, use cases for each role, and teams that know how to carry on alone.
03
Equip
A PAI for each role
- Who it’s for
- A person or a business team.
- The problem
- A generic assistant knows nothing about your work, your tools or your documents.
- What we do
- A PAI (Personal AI Infrastructure) dedicated to a role, the way you’d equip someone with a computer. It brings together a central assistant, context, tools and sub-agents. Two options: Claude (including Cowork and Claude Code), our specialty; or a sovereign alternative, with OpenWebUI, OpenCode and inference hosted in France.
- What you keep
- The configuration, the context and the procedures, in open formats.
04
Write
Your know-how as Skills
- Who it’s for
- Teams whose know-how makes the difference.
- The problem
- That know-how is often tacit, and an agent can’t use it until it’s written down.
- What we do
- We write Skills with the people who hold the know-how, never behind their backs. Then we deploy them, and SolidSkills manages their lifecycle.
- What you keep
- Your Skills, in an open format, usable with other models and other agents.
05
Embed
An embedded AI engineer (FDE)
- Who it’s for
- Organizations that want to launch or speed up the adoption of agents.
- The problem
- The tools are bought, but usage doesn’t take off, or stalls after the first enthusiasts.
- What we do
- A dedicated engineer works within your teams (Forward-Deployed Engineer). They launch adoption, or speed it up if you’ve already started, then follow the rollout. As interested in ways of working as in the technology.
- What you keep
- Self-reliant teams, and documentation of everything that was set up.
What we don’t do
- 01Replace a team with agents fed on its know-how.
- 02Write down someone’s know-how without them.
- 03Test on you what we haven’t tried on ourselves.
- 04Make you dependent, on a vendor or on us.
Let’s talk about your know-how.
Thirty minutes to see whether, and how, we can help you put your know-how to work with AI. If we’re not the right fit, we’ll tell you who is.