A cloud copilot sends your data to someone else's model and only sees the one app it lives in. NodePlus runs on local models on hardware you control, and reads across every system you run.
Same command surface across finance, sales, operations, and HR, with a coding engine that builds its own integrations. Private by default, $0 per token, frontier-class results.
The gap is not features. It is architecture: where the model runs, how much it can see, and who controls it.
A copilot is useful inside its app. NodePlus is built for the work that spans systems and touches data that cannot leave.
The model runs on your hardware. There is no third-party provider in the loop and no data sent out for inference.
Reads across the systems you already run, so answers span finance, sales, and operations instead of one app.
The coding engine writes the connectors between your systems, work a copilot cannot do and a shop quotes in quarters.
66.6% on SWE-bench Pro. It writes and repairs real features against your stack, end to end.
You control the stack, the data boundary, and the audit trail, with no opaque provider between you and your data.
A single command surface for the whole business instead of a separate copilot and bill for every tool.
Two structural differences. NodePlus runs on local models on hardware you control, so your data never leaves the building, and it reads across every system you run rather than living inside one app. A cloud copilot sends your data out and only sees the app it is bolted onto.
Only through prebuilt plugins, and only by sending that data to the provider. NodePlus builds its own connectors with a coding engine that scores 66.6% on SWE-bench Pro, and it does the integration locally.
It ships working code. The same engine writes and repairs features, builds the connectors between your systems, and produces the reports you ask for, against your stack. It is a working system, not an autocomplete.
Not quality. NodePlus lands among the leaders on the public coding and memory benchmarks, on local models. What you give up is per-token bills, data egress, and dependence on a provider you cannot audit.
Operators who run real systems and cannot send that data to the cloud: regulated businesses, firms with residency obligations, and teams that want one AI surface across finance, sales, operations, and HR rather than a copilot per app.
Book a briefing and we will scope a deployment against your systems, on local models you control, with no per-token bills.