The problem
A capable model can work through a new problem. It does not automatically know your earlier decisions, the reasons behind them or the limits you agreed with another tool.
That gap makes people repeat background and supervise the same mistakes. Our focus is the durable layer around the model: context that belongs to someone, can be inspected and can inform future work.
The platform and the ambition
thinqOS is the cognitive layer for AI. A Mind holds context outside the model. Agents can use it with connected tools. People can correct it and decide what responsibilities to delegate.
We start with owner-run businesses whose recurring work depends on account history, current records and earlier commitments, beginning with buyer and account follow-up. A small group of developers tests how well context carries between AI tools. Over time, every person and agent a business runs gets a Mind of its own.
Built by AI4Outcomes
thinqOS is an AI4Outcomes product operated by DeMers IT Inc. Daniel DeMers leads product and Jennifer DeMers leads operations.
We use AI agents in our own work. That gives us problems to test and failure modes to investigate; it is not a substitute for independent customer evidence.
Judge the work, not just the vision
Theory explains our ideas and the limits of the supporting evidence. The context study includes the result that challenged our then-current configuration. The product remains in private preview.
If you are evaluating thinqOS for use, investment or another collaboration, start with the platform and the evidence. Request access to discuss the specific work you want to examine.
