Product
One platform, and the modules over it.
Contour resolves the systems you already run into one governed model of your business, then serves that model to your team and to the agents they work alongside, over MCP. The platform itself is domain-neutral. Modules take it deeper, into the areas where an answer has to understand equipment and instruments rather than only tables.
Model Context Layer
Connect the assistants and agents your team already uses to your business, over MCP. They answer from verified operations rather than from a query they wrote themselves, and every figure carries lineage back to source.
Asset Tree & Failure Propagation
See what a single failure takes down with it. Contour models the plant as a dependency graph rather than a list of tags, so consequence can be traced to the production it costs you.
Reliability Engineering
Plan against the outage you are actually scoping. Each asset's own failure history is fitted with established reliability statistics and becomes a probability of failing inside the window you set, ranked by what that failure would take with it.
Sensor Intelligence
The layer the other two stand on. Contour ingests instrumentation continuously and resolves every tag to the equipment it measures, which is what lets a decade of time series be read against a decade of failures at all.
What the modules have in common
Every module reads the same model and answers through the same interface. There is no separate integration per module and no second copy of your data: the asset tree, the reliability estimates and the sensor history are all descriptions laid over sources you already run, so a question can cross between them without leaving the model.
They share the same limit too. Contour answers only what the model describes, and a question falling outside it comes back as a refusal rather than an inference. That constraint is what makes the rest usable, because an answer you do receive is one the model could account for.