From pages to tasks
Readiness depends on whether a real goal can be completed, not only whether a page can be crawled.
We are creating evidence-based quality assurance for a customer channel that websites were not originally designed to serve.

A website can be technically available yet fail when an agent must compare options, understand a control or complete a task. Aiscovery connects those failures to step-by-step evidence and practical fixes.
AI discovery, browser agents and structured tools are becoming additional paths into digital products. Teams need a way to inspect the experience without treating every model error as a website defect.
Readiness depends on whether a real goal can be completed, not only whether a page can be crawled.
Results must retain agent, model, policy, viewport and environment context.
A useful finding needs an observed result, reproduction path and verifiable final state.
The methodology is designed to remain useful as agents, interfaces and emerging standards change.
Critical customer journeys carry more weight than a long checklist of low-impact signals.
Literal checks decide a result. An AI check may only confirm it or flag it for review from the same evidence, never turn a failure into a success.
Authorization, stop gates, redaction and test environments are part of the run contract.
Every failure is attributed to your website, the agent, a policy boundary or our platform. Platform failures are ours and never count against your site.
Aiscovery owns the check definitions, evidence contract and verdict rules. Website owners define expected outcomes and authorize scope. Agent vendors remain responsible for their models and policies.
Aiscovery is available on paid plans and works closely with a small group of design partners. Public copy separates what runs today from what is marked Coming later.
The clearest way to contact the team is a launch-partner application with the website, workflow and expected outcome in scope.