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 replayable evidence and practical remediation.
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.
Deterministic assertions lead. Model judgment is reserved for subjective checks and must reference evidence.
Authorization, stop gates, redaction and test environments are part of the run contract.
Website, agent, policy and infrastructure failures are reported separately.
Aiscovery owns the audit definitions, evidence contract and scoring logic. Website owners define expected outcomes and authorize scope. Agent vendors remain responsible for their models and policies.
Aiscovery is in a partner-led private beta. Public copy distinguishes what can be reviewed today from monitoring and broader self-service capabilities that remain roadmap work.
The clearest way to contact the team is a launch-partner application with the website, workflow and expected outcome in scope.