AI Lab
Every product was born here. Every project leans on it.
Thinkia is a services company that happens to have products, and both come from the same bench. Before there is a client, a budget or a name, there is a question nobody has answered yet — the lab is where we take it apart. Some of what happens here never leaves the bench. The rest is on sale today, or already inside the work we deliver.
The products are just the part with a name on it. Most of what the bench produces has no brand and no price: the failure we already hit, the approach we already discarded, the number we already measured. That is what a project of ours starts with, and it is the difference from a generic implementation.
How it comes out
Each line follows one question. When an answer holds up outside the bench, it leaves as a product — and keeps the line it came from. One line has not got there yet, and that is the normal state of a lab.
Line 01
What can a system decide on its own?
Autonomy and orchestration: how many agents share a goal, hand work to each other and stay governable while they do it.
On the bench now
Left the bench as
Line 02
What does a company actually remember?
Retrieval, structure and memory: turning scattered documents into something a system can reason over instead of merely search. The engine underneath is our own — RAGXplorer — and it answers with the document, the chunk and the confidence score attached.
On the bench now
Left the bench as
Line 03
What does AI look like when a person meets it?
Voice, face and conversation: the surface where a system stops being infrastructure and becomes an interaction someone remembers.
On the bench now
Left the bench as
Line 04
What has to be true before this runs in production?
Governance, traceability and security: the work that decides whether a prototype is allowed anywhere near a real operation.
On the bench now
Left the bench as
Line 05
Can this run on our own hardware, with our own models?
Smaller models that hold up, prompts that are compiled instead of written, and serving tuned to your own machines — so data sovereignty stops being a reason not to deploy.
On the bench now
Left the bench as
Nothing has left this line yet.
The rule
Work starts from something we cannot answer yet, not from a feature someone asked for.
The prototype exists to fail somewhere specific. Where it fails is the finding.
It only becomes a product when it survives governance, cost and operation — not when it looks good in a demo.
Everything the lab has taken all the way through is in the product catalogue.
