About Aiscovery

Building a more reliable web for agents and people.

We are creating evidence-based quality assurance for a customer channel that websites were not originally designed to serve.

A verified AI-agent journey connecting website interfaces, structured evidence and a completed outcome

Make agent journeys observable, testable and safer to improve.

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.

The interface is changing. The responsibility stays with the website owner.

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.

From pages to tasks

Readiness depends on whether a real goal can be completed, not only whether a page can be crawled.

From one browser to many executors

Results must retain agent, model, policy, viewport and environment context.

From scores to evidence

A useful finding needs an observed result, reproduction path and verifiable final state.

Product principles guide every audit decision.

The methodology is designed to remain useful as agents, interfaces and emerging standards change.

Tasks before vanity metrics

Critical customer journeys carry more weight than a long checklist of low-impact signals.

Evidence before inference

Deterministic assertions lead. Model judgment is reserved for subjective checks and must reference evidence.

Boundaries before automation

Authorization, stop gates, redaction and test environments are part of the run contract.

Specific causes before generic blame

Website, agent, policy and infrastructure failures are reported separately.

One method, with explicit layers of responsibility.

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
Scenario definitions, controlled execution, evidence collection, evaluation and reporting.
Website team
Business expectations, access boundaries, fixtures, acceptance criteria and remediation ownership.
Agent provider
Model behavior, product policy, tool availability and vendor-specific limitations.

Built privately, described honestly.

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.

Current focus

  • Scoped readiness audits for selected partner workflows
  • Browser, search and agent-native technology assessment
  • Session evidence, timing, CLS and prioritized remediation

What we do not claim

  • Guaranteed rankings, citations or permanent agent compatibility
  • Unauthorized testing or irreversible production actions
  • Public self-service access before the workflow is ready

Bring us one journey worth testing.

The clearest way to contact the team is a launch-partner application with the website, workflow and expected outcome in scope.