Buyer FAQ
A. How accurate is a Snapshot?
Three things are independently auditable, and none of them depend on trusting the analysis node.
- Raw response fidelity. Every datapoint is the verbatim LLM response, with a timestamp and a public URL in the audit-log repository. You can click through and confirm that the report's claim matches the raw response. Verifiable, not estimated.
- Mention and coverage math is deterministic. The per-endpoint and per-category counts are computed by the orchestrator from the raw responses, not regenerated by an LLM. The same raw JSONs always produce the same numbers. Reproducible.
- Interpretation is locked to 6 rules. The analysis node is constrained by methodology.html §9 (no "best", no "guaranteed", no invented citation URLs, no competitor rankings, no percentage headlines, no missing Data Provenance footer). A violation forces a re-draft before delivery.
The AI-readable Markdown brief's YAML frontmatter carries a confidence: high | medium | low field, computed by the orchestrator from endpoint completion. The score is deterministic and reproducible; it is not generated by an LLM. We do not claim guaranteed accuracy in the sense of 100% right about your future rankings. We claim verifiable raw responses, reproducible math, and a fail-closed delivery QA gate. For the full breakdown, see methodology.html §11.
B. Which model endpoints are covered?
Today, Snapshot covers 7 production model endpoints across two openness surfaces: open-weight/source-available endpoints (Kimi, DeepSeek, Qwen) and closed proprietary API endpoints (Doubao, ChatGPT, Claude, and Gemini with Google AI Overviews). All tested models are multilingual. The grouping describes model openness and auditability surface, not geography or language capability.
All 7 run via documented API methods with the data-retention and training-control posture recorded per datapoint. This is an API audit, not a product-surface audit — we measure what each underlying model returns on a controlled prompt, not what a signed-in user sees inside the ChatGPT or Gemini app. See methodology.html §6 for what is in scope and what is not.
Why not cover every model? Adding an endpoint is a real commitment: API access, data-retention controls, training-control posture, DPA terms, a tested adapter, a reproducible request payload, and a per-datapoint raw JSON to keep the methodology contract honest. We will not silently swap endpoints that lack a reviewed data-control posture or a tested adapter — that would force customers into a privacy posture they did not sign up for.
The current production list does not include ERNIE, MetaSo, or Perplexity Sonar; the historical Day-1 self-audit at /audit/self-audit-01.html used a broader experimental matrix and is kept for transparency. "All AI models" is not a stable target — new models appear weekly, vendors retire models without notice — so adding an endpoint is a versioning event with a methodology changelog entry, not a marketing update. For the current production matrix and the model-freshness policy, see methodology.html §1 and §7.
C. What do I actually receive?
Three files:
- A 1-page human PDF for leadership.
- An AI-readable Markdown brief for your internal AI agents or your Obsidian vault — with stable finding_id, evidence_id, and action_id identifiers, so an AI can summarize without paraphrasing.
- A raw-data index that links to every LLM response for independent verification.
Every report also includes deterministic GEO scores: AI Citation Readiness and Source Trust Baseline. For repeat customers, Clarivy can load sanitized repeat-audit memory so future audits compare against prior runs without storing contact details, billing data, raw responses, or raw JSON in memory.
Every claim in the human PDF cites a raw JSON line. A sanitized, fictional sample of all three files is at /audit/sample/ — the numbers in that sample are mock, the deliverable shape is real. We publish it so you can see what you are buying before you buy it. Snapshot is one input among many; it is not a substitute for user-research interviews, conversion analytics, an SEO backlink audit, or a brand-tracker survey. See methodology.html §4 and §11.5 for the full delivery package and what "decision-grade" means in practice.
D. Is a Snapshot enough?
A Snapshot is enough if you want to risk-screen a known query, spot-check a category entry, or baseline a brand before a larger engagement. It is not enough as a category-wide audit; its cover page states "quick diagnostic, not a complete audit".
Standard and Enterprise are the planned deeper audit products — coming soon, no public price today. When they ship, Standard will use a 120-prompt stable matrix on the same 7 endpoints with named authorship and prioritised actions, and Enterprise will add a multilingual sweep plus a quarterly refresh for 12 months. Until then, Snapshot is the only audit product you can buy from Clarivy. The 30-day refund covers the case where Snapshot misses any of the 5 queries you specified at purchase.
The audit is one input. It is not a substitute for user-research interviews, clickstream / conversion analytics, an SEO backlink audit, or a brand-tracker survey. You decide how to combine it with the rest of your evidence. See methodology.html §5 for what Snapshot does and does not cover, and methodology.html §11.5 for what "decision-grade" means for a buyer.
E. Is the audit process professional?
Treated as a regulated analytics deliverable, not a marketing artifact. Three concrete gates:
- Analysis node is locked. methodology.html §9 lists the 6 non-negotiable rules (no "best" / "only" / "guaranteed" / "always" about Clarivy or competitors; every claim cites a raw JSON; no percentage in headlines; no invented citation URLs; no ranking of competitors; Data Provenance footer on every report). A violation forces a re-draft before delivery.
- Delivery QA is fail-closed. methodology.html §8 lists 5 gates (PDF render, AI-readable Markdown brief schema, raw-data count, public link check, partial-rate gate at > 20% missing). A draft that fails any gate is held for human review; the customer is told, not silently sent a broken deliverable.
- Reproducibility is verifiable. Every report links to a dated folder in the public agentgeek-geo/audit-logs repository. You (or any auditor) can clone it, replay the orchestrator against the same prompts, and diff the result.
The operating entity is documented on the Legal operator page. The 30-day refund covers the case where Snapshot misses the 5 queries you specified at purchase. We do not publish aggregateRating or customer-count schema on this site; we will not, until we have 50+ real customers with their own written consent to be cited.
F. After the audit, is there an action plan?
Yes. The AI-readable Markdown brief ships with prioritised actions and a 30-day implementation plan. Every action links to at least one finding_id and one evidence_id, so you can trace every recommendation back to a specific (endpoint, query) datapoint. Actions are ordered by lift-per-effort, not total lift, so a small marketing team can execute the top two in a week and see the next monthly run start to move.
The audit is one input. It is not a substitute for user-research interviews, clickstream / conversion analytics, an SEO backlink audit, or a brand-tracker survey. You decide how to combine it with the rest of your evidence.
A Continuous Monitor add-on (on the roadmap; not for sale today) will, when launched, auto-generate a fresh audit plus a delta narrative each month using agreed prompt sets and sanitized same-customer memory, so the improvement loop is verifiable. We do not promise a specific revenue or traffic lift; the Princeton 2023 paper reports +40% visibility in a controlled setting, but individual results vary widely. The audit is an analytics instrument, not a guarantee of business outcomes. See methodology.html §11.5 for what "decision-grade" means in practice.
G. Why $149 for a Snapshot?
$149 one-time is the only public price on Clarivy today. It covers the assurance package: multi-endpoint data collection, raw evidence traceability, the human PDF, the AI-readable Markdown brief, deterministic GEO scores, the raw-data index, delivery QA, repeat-audit memory for future Clarivy runs, and the methodology contract.
| Audit product | State | Math | Datapoints | Delivery | Price |
|---|---|---|---|---|---|
| Snapshot | Active | 5 queries × 7 endpoints | 35 | 1-page PDF + AI-readable Markdown brief + raw-data index, 48 h | $149 |
| Standard | Coming soon | 120 prompts × 7 endpoints (planned) | 840 (planned) | Planned: 5-notebook PDF + brief + raw-data index, 7 business days | Price hidden — to be announced at launch |
| Enterprise | Coming soon | 120 × 7 endpoints × 5 query languages (planned) | 4,200 (planned) | Planned: 8-notebook PDF + brief + raw-data index, 12-month quarterly refresh | Price hidden — to be announced at launch |
Continuous Monitor is on the roadmap and is not part of the current product contract — it is not for sale today. When it ships, it will be a voluntary monthly add-on; the launch price will be confirmed on the launch announcement.
The 30-day refund is the price floor — if Snapshot misses any of the 5 queries you specified, we refund in full. We do not put sales pitches inside the report. We do not advertise a "starting from" price. We do not advertise "12+" endpoints. We do not advertise aggregateRating or customer-count schema markup. We do not advertise SOC 2 or ISO 27001 until we have them; we say "not yet, target H2 2026 / Q4 2026" instead. See methodology.html §1 (the product table) and methodology.html §5 (Snapshot's scope).
Related pages
- /audit/methodology.html — the technical contract: 7-endpoint matrix, 3-file delivery package, Snapshot vs planned Standard / Enterprise, API vs product surface, Model freshness policy, Delivery QA gate, the 6 anti-hallucination rules, §11 Confidence / accuracy / limitations.
- /audit/self-audit-01.html — Day-1 self-audit (historical dogfooding artifact; current production matrix is different). Kept for transparency.
- /#trust — Trust and transparency block on the landing page (documents, compliance status, public proof links).
- /#pricing — the Snapshot Audit ($149, available today) and the Coming-soon Standard / Enterprise placeholders.
- /zh/audit/faq.html — the Simplified Chinese mirror of this page.
Changelog
- v1.0 (2026-06-15) — initial release. 7 buyer questions (accuracy, decision-grade, model endpoint coverage, model freshness, professionalism, post-audit improvement, price).
- v1.1 (2026-06-16) — P0 product-status reset. Snapshot is the only product buyable today ($149 one-time). Standard and Enterprise are planned deeper audit products — coming soon, no public price today.
- v2.0 (2026-06-16) — P1 rewrite. Cut from the "we commit to" voice to plain customer-first language. Reframed the 3-file delivery as human PDF + AI-readable Markdown brief + raw-data index (the brief's full name replaces the earlier internal shorthand in the customer surface). Renamed "is the result safe to use as a commercial decision input?" to "is a Snapshot enough?" so the buyer-objection map is led by buyer questions, not by our engineering decisions.
- v2.1 (2026-06-16) — P2 split. English-only content on this page; Simplified Chinese mirror moved to /zh/audit/faq.html. No copy change beyond the language separation.
- v2.2 (2026-06-17) — Reframed coverage from language-labelled coverage wording to production model endpoints. Clarified that all tested models are multilingual.
- v2.3 (2026-06-18) — Reframed endpoint grouping to open-weight/source-available versus closed proprietary API model surfaces.
- v2.4 (2026-06-19) — Added deterministic GEO scores, sanitized repeat-audit memory, and Continuous Monitor continuity language to match Privacy Policy v1.1, DPA v1.1, Terms v1.1, and Methodology v2.9.