I built GAAI after handing real work to AI agents — not demos, software I actually needed to ship. The agents were fast. They were also fragile. Every new session missed decisions I had already made. Every new tool started from partial context. The faster the agents worked, the more obvious the real problem became: the model was powerful, but the project memory was not.
So I started with governance: scope, rules, verification, audit. One primitive kept carrying the others: memory. Not personal preference memory. Project memory — the decisions, constraints, rules, tradeoffs, and working truth of how the project actually runs. When that memory was durable, agents became more useful. When it was scattered, they went back to guessing.
That pain is not mine alone, and it is not only about code. Anyone doing serious work with AI lives it. You use one tool for research, another for writing, another for planning, another for implementation. None of them naturally share the project truth. The human becomes the transport layer: carrying context between tools, sessions, teammates, and clients.
Something changed underneath all of this. Inference is becoming a commodity. Better models ship constantly. Everyone can rent the same intelligence by the hour. As that happens, the durable advantage is not which model you used this month. It is what your project has learned and whether your agents can use it at the right moment.
GAAI exists because project memory should not be trapped in a vendor chat, a local note, a teammate's head, or a tool-specific memory you lose when you switch. The model is rented. The compute is rented. The project context you accumulate is the asset. That asset has to be:
Portable. It lives outside any single AI tool and follows the project across the tools you already use.
Governed. Permissions, scope and audit decide what can be retrieved, by whom, and why.
Shared. Every compatible tool and teammate can work from the same project truth instead of rebuilding a private copy.
GAAI Cloud is that governed project-memory layer. It does not run your model. It does not replace your tools. It is not in the inference path. Your AI tool keeps talking to its own provider; GAAI holds the project memory your tools should be able to retrieve.
The mission is simple: make real work with AI agents more reliable by giving them the right project context at the right moment, with governance humans can inspect.
Models will change. Tools will change. Keep what your project learns.
Frédéric Geens
Founder, GAAI Cloud · June 2026