Reporting
Immutable, period-scoped reports that capture AI visibility change, deployments made, and measured outcomes — shareable with clients and presentable under agency branding.
What a report contains
A GeoScript report is an immutable, period-scoped snapshot. It captures AI visibility observations across the reporting period, the deployments made and independently verified, and the measured change in visibility attributable to those deployments. Reports are structured around four narrative sections — what was measured, what changed, what was deployed, and what the evidence shows — all grounded strictly in observation data from the reporting period.
Immutability: why it matters
Once published, a report snapshot cannot be altered. The numbers a client sees in a report are frozen at publication time and remain permanently accessible at a stable, shareable URL. This matters for agency credibility: clients know the report reflects what actually happened, not a retroactively adjusted presentation. GeoScript enforces immutability at the database level — published snapshots are write-locked.
White-label distribution
Reports are agency-branded: the client-facing public report page is presented under the agency's identity, not GeoScript's. The agency's identity governs the presentation; GeoScript's infrastructure powers it. White-label distribution as a fully self-managed capability (agency-controlled branding, custom domains) is planned for a future phase.
Honest evidence depth today
Report evidence depth is currently constrained by the AI monitoring layer: three of six planned engine adapters are live with real API observations. The other three — Gemini, Google AI Overview, and Copilot — are in development. Reports today reflect the observation signal from the three live engines; breadth will expand as more engine integrations ship. GeoScript surfaces this limitation in reports rather than obscuring it.
Ask GeoScript: the natural-language interface
Reports are the grounding layer for Ask GeoScript — GeoScript's natural-language interface for answering client questions about their AI visibility data. Ask GeoScript answers questions strictly from the client's own observations, snapshots, and reports. It does not speculate, does not fabricate data, and refuses to answer when the workspace has no relevant evidence.
How this connects to the full loop
Reporting closes the product loop. Observations from the AI Visibility layer feed in; deployment records from the Optimization layer feed in; the report packages these into a client-facing narrative. The next cycle begins with updated observations — the same loop, with a richer evidence base. Agencies can deliver a report at the end of every period and begin the next with data that accumulates on the prior period's foundation.
What Reporting is not
Explicit limitations (§127)
- ✕GeoScript reports do not claim causal attribution — they measure before-and-after AI visibility observations and report the difference; correlation is not guaranteed to be causation.
- ✕Evidence depth is currently limited to the three live engine adapters (ChatGPT, Claude, Perplexity). Gemini, Google AI Overview, and Copilot observations will appear when those integrations ship.
- ✕White-label with full agency-controlled branding and custom domain is planned, not yet available.
- ✕Ask GeoScript is available in the agency console for grounded Q&A; a public-facing docs Ask interface is not yet available.
- ✕GeoScript reports do not include traditional SEO metrics, website traffic, conversion data, or advertising performance.
Related
Other pillars
Monitor how AI engines respond to the queries that matter for your clients — capturing mentions, recommendations, and citations across a prompt universe built around each business.
Find businesses with measurable AI visibility gaps, score each opportunity, track your pipeline, and deliver evidence-backed pitches — before a competitor does.
GeoScript crawls a client's public website, extracts a structured content evidence base, and builds the Content Genome that powers every recommendation.
Understand which AI crawlers and agents are reaching a client's site, what they're doing, and why — with verified identity and declared purpose.
Turn Content Genome findings into specific, typed recommendations — then deploy them through an approval-gated, verifiable system that leaves an immutable record.
Every observation, recommendation, and outcome lives in a structured, tenant-isolated, immutable-where-it-matters data architecture — the evidence base the entire platform reasons over.