P10GEO Auditor

P10 GEO Auditor

P10 GEO Auditor

P10 GEO Auditor is the agency platform for measuring and improving AI-era visibility across model answers, search surfaces, and supporting source ecosystems.

It is built for controlled, repeatable audits: scoped by organization, team, project, and site; backed by invite-only access; and designed so every recommendation can be traced to evidence.

Visibility Coverage

Evaluate representation in AI outputs, source citations, and search-surface placements across prioritized geographies and query classes.

Operational Controls

Manage teams, projects, sites, schedules, and role-based access with invite-first onboarding and auditable account changes.

Evidence Traceability

Preserve recommendation lineage with captured observations, structured metadata, and action logs for review, QA, and stakeholder reporting.

Process Depth At A Glance

A high-level view of audit complexity and validation depth derived from the narrative run architecture.

20+

Stage Gates

Narrative flow checkpoints from intake through learning feedback

3

Model Authority Lanes

Primary, challenger, and fallback analysis chain

3

Extraction Passes

Strict, lenient, and fallback signal extraction modes

4

Primary GEO Layers

Coverage, diversity, authority, and concentration anchored by technical quality

2

Search Surfaces

Google and Bing enrichment paths when enabled

9

Learning Signals

Profiles, facts, hypotheses, families, deterministic deltas, outcome deltas, lifecycle outcomes, memory, and scoring history

3

Tuning Controls

History-gated tuning status, robustness guardrails, and optional bounded safe-apply policy

Built for Repeatable Improvement

GEO performance is tracked across repeated runs so teams can compare results over time, identify priority actions, and validate improvement with clear evidence.

Recommendation outputs are kept client-actionable even when noisy runs occur, and tuning guidance is constrained by site-history robustness guardrails before any bounded apply policy is used.

Each run is structured for operational follow-through: auditable outputs, accountable ownership, and measurable progress.