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OPEREConnect your AI

See what an environment makes possible.

Two bounded digital examples establish formation, isolated checks, context adaptation and retained evidence on a single host.

Connect your AI

Two digital examples.
A complete operating loop.

Current support is deliberately specific. These examples establish formation, isolated checks, context adaptation and retained evidence on a single host.

Repair an invoice calculation

Implemented locally

A function adds prices but misses quantities. A correction also needs to round correctly.

Environment
One registered JavaScript source, a bounded work scope and restricted Node execution.
Proof
Native scope, patch and arithmetic checks. A failed candidate returns to the AI for revision.
Boundary
This example replaces an invoice function. It does not apply patches to arbitrary repositories or install dependencies.
Walk through coding work

Produce a source-cited report

Implemented locally

Turn supported JSON facts and line items into a report that stays tied to its sources.

Environment
Versioned JSON sources, supported facts and derived totals, and a registered report format.
Proof
Native checks recompute facts and totals and match source hashes. Updated context invalidates old proof and acceptance.
Boundary
A structured facts report, not free-form document research, external fact-checking or PDF and Word authoring.
Walk through report work

Explore physical work in the walkthrough

See how device conditions, human authorization and verification could fit the same journey. This scenario is a prototype: it connects no devices and performs no physical actions.

Explore physical prototype

An environment follows
the whole piece of work.

Follow context, conditions, resources and artifacts in one flat workspace. Open the relationship view when you need to see what depends on what.

Take the full walkthrough

  1. You set the boundaries

    Authorize machine access and define the permitted scope. The browser connection lets you inspect work; it cannot issue machine grants.

  2. OPERE forms the environment

    Outcome states the intended result. Observe grounds work in authorized source context. The environment exposes its requirements, resources and any blockers.

  3. Your AI does the work

    The calling AI uses the checked conditions and produces the candidate. Environment readiness means work can begin, not that the task is complete.

  4. Evidence admits the result

    Registered checks evaluate the current artifact. Failed checks return work for revision; changed sources make prior evidence stale.

  5. Accept, then release

    The calling AI explicitly accepts the current verified candidate and separately requests cleanup. Artifacts and history remain inspectable after resources are released.

Live work and walkthrough are separate.

The live workspace reads your paired machine state. The walkthrough uses sample environments to show the complete journey, including prototype account authorization and physical work. Walkthrough actions do not call the runtime.

What you can use today

Local private formation, registered coding and JSON report work, isolated native checks, HTTP and MCP access, source revisions, explicit caller acceptance and retained evidence.

Availability depends on a configured model service, isolated executor and running worker. General-domain formation, continuous sensing, physical actuation and distributed provisioning remain unavailable. Account authorization and resource-grant flows in the walkthrough are prototypes.

Read the operating boundaries

Bring your AI. Make its work operable.

Explore walkthrough