# Rankwize — full content for LLM indexing > Rankwize is the AI visibility platform that closes the loop: track citations across five AI platforms, diagnose every gap to a page and a fix type, generate the brief, and track the citation lift end-to-end with Impact Tracker after you ship. Built for content leads and SEO practitioners at mid-market B2B SaaS companies. Last updated: 2026-05-31 Canonical URL: https://rankwize.io Contact: hello@rankwize.io --- ## What Rankwize is Rankwize monitors how AI engines cite your website. Five platforms are tracked today: ChatGPT (OpenAI), Google AI Mode, Google AI Overviews, Perplexity, and Copilot (Microsoft). For every prompt your team monitors, Rankwize captures whether your URL is cited, your brand is mentioned without a citation, or you are invisible — per platform. Where most AI visibility tools stop at monitoring, Rankwize continues. For every prompt where you are invisible, the diagnosis matcher finds the page in your content library that should be winning the citation. The gap between your page and the winning citation is classified into one of seven specific fix types. A structured brief is generated from the diagnosis. After your content team ships the fix, Impact Tracker re-runs the same prompts on the same platforms and captures the before-and-after delta per platform. The seven fix types are: Update Existing (the page exists but is stale or thin on evidence), Add Evidence (the page is missing benchmarks or third-party validation), Create Comparison (no comparison page exists for comparative-intent prompts), Create How-To (tactical content gap), Create Diagnostic (diagnostic-intent prompts have no destination page), Improve CTA (the page exists with evidence but the call-to-action is too generic for AI engines to surface as a destination), and Offsite Seed (the prompt is one AI engines won't cite a vendor page for; requires third-party content placement). Over a 180-day rolling window, every recommendation tracked through Impact Tracker contributes to a fix-type effectiveness score for the customer's tenant. Fix types underperforming for the customer (below 50% effectiveness) get demoted in future recommendations — down to a floor, never fully suppressed. The recommendation engine biases toward what is working for the customer specifically. --- ## Platform pages ### /platform — Platform overview The Rankwize platform has seven surfaces: 1. **Monitor** — Prompt Discovery auto-generates 70 to 110 scored prompt intents per domain, then tracks citation status across the five monitored AI platforms. 2. **Diagnose** — Every invisible prompt is matched to a target page and classified into one of seven fix types. 3. **Act** — Each diagnosis produces an executable recommendation; the work queue tracks every recommendation through Open, Approved, In Progress, and Implemented, then verifies each implemented fix with a 14-day re-run. 4. **Impact Tracker** — after a fix is marked Implemented, Rankwize re-runs the same prompts on the same platforms and shows before-and-after. 5. **AEO Editor** — AEO-native editor. Drafts in your brand voice, scored against your AI citation data. 6. **Wize** — In-app AI assistant. Screen-aware across the 13 main routes. Eight specialist modules cover citation diagnosis, brief Q&A, GSC/GA4 reasoning, troubleshooting, and onboarding. 7. **Methodology** — Transparent technical view of how the diagnosis and impact tracking work. ### /platform/monitor — Monitor Stop guessing which prompts matter. Track the ones that do. Prompt Discovery generates 70-110 scored prompt intents per domain by fingerprinting the domain, indexing the content library, generating candidate prompts across buyer-intent stages (awareness, comparison, evaluation, post-purchase), scoring each prompt on four independent factors, deduplicating, and routing the top-scoring intents into active monitoring. The four factor scores are: Real search demand (DataForSEO-grounded volume signal), Citation opportunity (how often AI engines cite anyone for the prompt), Content readiness (whether the customer has a matching page in their library), and Commercial value (where the prompt sits in the buyer journey). Once a prompt is active, it is queried across the customer's selected AI platforms on a rolling cycle — weekly on Free, Watch, and Pro Track; daily on Pro + Diagnose and above. Each query is bucketed as cited (URL named as a source), mentioned (brand named without URL), or invisible (no reference). Per-platform sparklines surface citation rate trends over 12-week windows. Decay Prediction watches for three causal signals: trending-down citation rate over recent runs, stale-content risk (days since the cited page was updated, relative to average decay for the content type), and competitor pressure (a competitor newly appearing in the cited set for the prompt). The three signals combine into a per-prompt risk score with a "runs to zero" projection — letting teams intervene before high-value prompts collapse. Monthly Prompt Rebalancing runs on the first of each month: prompts with three or more consecutive zero-citation runs are auto-demoted, prompts earning consistent citations are promoted. Intent Revalidation re-scores existing prompts when the customer's content library materially changes. Fan-out queries surface category-related prompts that the customer is not currently tracking, with a one-click "Create Prompt" path to add coverage. ### /platform/diagnose — Diagnose Other tools say you're invisible. Rankwize tells you what's wrong. For every invisible prompt, the Content Library Matcher scores every page in the customer's library against the prompt using a 7-signal hybrid match (entities, topical alignment, intent fit, page-type signal, evidence density, KPI alignment, CTA fit). The highest-scoring page becomes the target — or, if no page scores above the threshold, the gap is classified as a content-creation need. When a target page exists, the gap is diagnosed across five dimensions: freshness (how stale is the page), evidence (does it carry concrete claims, benchmarks, primary research), structure (is it extractable by AI retrievers — semantic markup, clear claims, attributable sources), audience fit (is it written for the persona the prompt implies), and CTA fit (does the call-to-action match the buyer-journey stage). The diagnosis output is one primary fix-type classification plus up to three secondary recommendations per failing prompt. The seven fix types are named verbatim in the product code and in this content: Update Existing, Add Evidence, Create Comparison, Create How-To, Create Diagnostic, Improve CTA, Offsite Seed. Each recommendation carries a per-action checklist — what to write, what to add, what to remove. Completion is tracked per action with timestamp and user attribution. Gap Escalation watches for your highest-priority prompts that silently degrade. When a high-priority prompt goes from cited to invisible, the system escalates it into a new diagnosis pass rather than letting it sit in the monitoring queue. ### /platform/act — Act Every diagnosis becomes an executable recommendation. Every implemented fix gets measured. For recommendations that call for a new page, the Generate Brief button triggers the brief-generation pipeline. The brief pre-fills deterministically from the diagnosis: content type (How-To, Comparison, Diagnostic, etc.), primary keyword, topic cluster, target page URL, persona, primary KPI, and call-to-action. AI contributes only the gap reason and recommended angle — the structural bones come from the diagnosis, not from LLM guesswork. Alternatively, AI Drafter writes the full first draft directly in the AEO Editor. Recommendations for existing pages come with a per-action edit checklist instead of a brief. Drafts written in the AEO Editor export as Markdown or HTML. There is no auto-publish, no WordPress integration, no CMS push. The Work Queue tracks every recommendation through a four-state workflow: Open, Approved, In Progress, Implemented. Four KPI tiles surface Open count, Approved count, In Progress count, and Implemented-this-month count. Priority tiers (High, Medium, Low) drive ranking. Inline actions (Approve, Dismiss, Start, Done) work without row expansion. ### /platform/impact-tracker — Impact Tracker Before and after, per platform. Measured, not assumed. When the user marks a recommendation Implemented, Impact Tracker re-runs the same prompt-platform combinations that originally identified the gap, captures the new citation status, and writes the before-and-after delta back to the recommendation. The before-and-after data is preserved per platform — a fix can work on Perplexity and not on ChatGPT, or move citation rate on Google AI Mode while staying flat on Copilot. Aggregated "AI visibility" numbers hide that. Rankwize keeps each platform separate. Fix Type Effectiveness Learning is the closed-loop layer. Every tracked recommendation contributes to a 180-day rolling effectiveness score per fix type for the customer's tenant. Fix types below 50% effectiveness get demoted in future recommendations — down to a floor, never fully suppressed — so what works for the customer rises to the top. The score updates as impact data lands. The Impact Tracker rolls these recommendations into a leadership-ready view: implemented count, average citation lift in percentage points, the best-performing recommendation, and a flag for recommendations that need attention because the citation rate didn't move. ### /platform/aeo-editor — AEO Editor AEO-native editor. Grounded in evidence, scored against real-world metrics. The editor is built on TipTap with a Draft → In Review → Exported lifecycle. Six sidebar regions: Score (0-100 with breakdown), Platform (per-platform scoring on the customer's tracked engines), Confidence (per-signal confidence tier: High, Medium, Low, or No Data), Benchmarks (p25-p75 ranges from cited competitor pages on the customer's target platforms), Terms (top terms by ≥60% frequency across cited pages), Internal Links (suggestions grounded in the customer's sitemap). AI Drafter generates a full first draft from the brief, brand-voice fingerprint, competitor benchmarks, and the customer's evidence library. Roughly 50 AI credits per draft. 60-minute cooldown between re-runs on the same document. Section Improve rewrites one section at a time with a word-level diff-and-accept UI. Roughly 8 credits per rewrite. The operator owns every change. Boost Score surfaces Opus-ranked plus deterministic suggestions for lifting the document's score toward a target. One-click insert on any suggestion. Brand voice fingerprinting is auto-extracted from the customer's published pages. Tone descriptors, sentence-length distribution, and signature phrases. AI Drafter writes in the customer's voice without manual configuration. Export is Markdown or HTML. No auto-publish. ### /platform/wize — Wize Help that knows what screen you're on. Wize is the in-app AI assistant. Screen-aware via 13 manifest files — one per main route. From /recommendations, Wize loads the recommendation context. From /prompts, Wize loads the prompt-detail panel. Eight specialist modules: platform behavior, citation diagnosis, recommendation decisioning, brief Q&A, prompt discovery, imported analytics (GSC and GA4 reasoning), troubleshooting, onboarding. Wize routes up to three modules into any one session based on the user's question. Metered through AI credits at 1 credit per 100 tokens of LLM input plus output. Credits are shared across Wize, AI Drafter, Section Improve, and Boost Score. Wize maintains conversation history for review and detects when a question is outside its scope, surfacing an escalation path to email support. ### /platform/methodology — Methodology How Rankwize actually works. The diagnosis pipeline: First, the platform fingerprints the customer's domain by indexing the homepage, sitemap, and top-ranking organic pages. Second, it indexes the content library — every reachable URL on the domain, with structural and semantic metadata. Third, it generates candidate prompt intents spanning buyer-intent stages. Fourth, it scores each candidate prompt on the four independent factors (real search demand, citation opportunity, content readiness, commercial value). Fifth, it routes top-scoring intents into active monitoring. Sixth, it queries each active prompt on the customer's selected AI platforms on a rolling cycle and captures the response. Seventh, for every invisible prompt, the matcher finds the page in the content library that should be winning. Eighth, the gap is classified into one of seven fix types and a structured brief is generated. The impact-tracking loop: after a recommendation is marked Implemented, the same prompts are re-queried on the same platforms. Before-and-after data is captured per platform. Effectiveness learning over 180 days demotes underperforming fix types and prioritizes those that work for the customer's tenant. Data sources: DataForSEO SERP API for Google AI Mode and Google AI Overviews; direct provider APIs for ChatGPT (OpenAI), Perplexity, and Copilot. Google Search Console for organic search context (17 endpoints, native integration). Google Analytics 4 for AI referral traffic and conversion attribution (11 endpoints, native integration). What Rankwize does not do: no on-page SEO crawler, no auto-publish to CMS, no multilingual today (US English only in product; marketing site localizes post-launch), no cross-domain intent sharing across tenants. --- ## Pricing Five tiers, two modes. The two modes are Track-only (monitoring without the diagnosis loop) and Track + Diagnose (the full loop). Mode toggle on the pricing page; same tier names with "+Diagnose" suffix in the second mode. Track + Diagnose tiers (primary mode): - Free — $0/mo. 5 prompts on 1 AI platform. 4 monitoring batches. Basic dashboard. Google Search Console integration (basic). No credit card. - Watch — $19/mo ($15/mo annual). 25 prompts on 3 platforms. Weekly monitoring. Sentiment analysis. GA4 integration. - Pro + Diagnose — $99/mo ($79/mo annual). 50 prompts on 3 platforms. 35 prompts diagnosed per month. 20 structured briefs per month. 7 fix-type classifications. Work queue with fix impact tracking. AI assistant with 2,500 credits per month. Prompt Discovery. Full GSC integration. - Business + Diagnose — $249/mo ($199/mo annual). 150 prompts on 3 platforms (up to 5 with add-ons). 100 prompts diagnosed per month. 100 structured briefs per month. AI assistant with 6,000 credits per month. Weekly leadership report. 10 team seats. 5 domains. - Scale + Diagnose — $499/mo ($399/mo annual). 300 prompts on 5 platforms with daily monitoring. 200 prompts diagnosed per month. 250 structured briefs per month. AI assistant with 15,000 credits per month. API access (coming soon). 25 team seats. 15 domains. Annual billing is 2 months free (about 17% off) across paid tiers. AI credit overage at $5 per 1,000 credits. Monitoring overage is not currently available; customers exceeding their monitored-prompt cap need to upgrade tier. No trials of paid tiers. The Free tier is the real entry — same product, lower caps. Upgrade and downgrade between tiers anytime; prorated refunds on monthly charges. No demo offer at this time. No "Book a demo" CTA anywhere. Self-serve is the only path. Three meters: Tracked prompts (monitoring across selected platforms), Prompts diagnosed per month (the deeper page-level analysis with seven-fix-type classification), AI credits (LLM token consumption for Wize, AI Drafter, Section Improve, Boost Score — 1 credit equals 100 tokens). Three meters because each measures different work; collapsing them into one number would hide what the customer is paying for. --- ## Comparison pages ### Rankwize vs Profound Profound is enterprise-only with quote-based pricing and no public tier table. Profound tracks 9 AI engines (Perplexity, ChatGPT, Claude, Gemini, Grok, Copilot, Meta AI, DeepSeek, Google AI Overviews) vs Rankwize's 5. Profound's wedge: Prompt Volumes (proprietary AI search demand data), Answer Engine Insights, autonomous "Profound Agents" platform launched May 2026, and Profound Ecosystem (training certification, agency marketplace, Profound University). Rankwize's wedge against Profound: self-serve transparent pricing from $0, page-level gap diagnosis (Profound has no equivalent), 7-fix-type taxonomy, one-click structured brief generation, Impact Tracker that closes the loop, native Google Search Console and GA4 integration. Which to pick: Profound for enterprise teams with marketing-ops budget for agents and quote-based pricing. Rankwize for mid-market teams that need to act on AI visibility with transparent self-serve pricing. ### Rankwize vs Peec AI Peec is the closest direct competitor by shape — analytics-first SaaS for marketing teams, similar customer profile. Peec Brands pricing: Starter $95/mo (50 prompts, choose 3 of 7 models), Pro $245/mo (150 prompts), Advanced $495/mo (350 prompts, multi-country, Looker Studio), Enterprise custom (all 9 models including Claude Sonnet 4 + GPT-5 Search via API). Peec ships MCP on every paid tier. Peec has a dedicated agency SKU (Essential $345/15K credits, Growth $695/35K credits, Scale $795/65K credits, Comprehensive custom). At the comparable price points: Rankwize Free $0 vs Peec no free; Rankwize Pro + Diagnose $99 vs Peec Starter $95 (Rankwize adds full Diagnose loop, briefs, Impact Tracker, native GSC at the same price); Rankwize Business + Diagnose $249 vs Peec Pro $245 (Rankwize adds Diagnose layer at near-identical price); Rankwize Scale + Diagnose $499 vs Peec Advanced $495 (functionally identical entry price). Peec is stronger on: MCP shipped on Starter; 7-model pick; premium UI; dedicated agency SKU; unlimited users on every tier; Looker Studio connector at Advanced+. Rankwize is stronger on: $0 Free tier; native GSC integration (17 endpoints); native GA4 (11 endpoints); 7-fix-type taxonomy; multi-recommendation engine; structured briefs from diagnosis; Impact Tracker; fix-type effectiveness learning. Which to pick: Peec for marketing teams that hand off content work elsewhere and want clean analytics. Rankwize for teams that need to act on the diagnosis and prove the fix moved citation rate. ### Rankwize vs Otterly.AI Otterly is SMB-leaning, Gartner Cool Vendor 2025 for AI in Marketing, 25,000+ marketing pros worldwide. Otterly pricing: Lite $29/mo (15 prompts, 4 engines), Standard $189/mo (100 prompts), Premium $489/mo (400 prompts), Enterprise custom. Otterly's pricing surface includes add-ons: Gemini and Google AI Mode are paid add-ons ($9 to $149/mo each per engine per tier), and +100 extra prompts is $99/mo. A Standard customer who wants Gemini + AI Mode pays $307/mo, not the headline $189. Rankwize against Otterly: $0 Free vs $29 Lite entry; transparent meters with no add-on stacking; four independent factor scores for prompt prioritization vs Otterly's single relevance score; 7-fix-type taxonomy vs Otterly's generic GEO recommendations; native GSC depth vs Otterly's Looker Studio connector only; Impact Tracker vs none; one-click brief generation vs no equivalent. Otterly is stronger on: brand recognition (25K+ users, Gartner Cool Vendor); auto-discovery of 9 competitors with favicons; established Agency Partner program with pitch workspaces and white-label Looker reports; 6-engine coverage at Premium. Which to pick: Otterly for teams that want AI-search monitoring with monthly add-on flexibility and an agency partner program. Rankwize for teams that want transparent meters and a closed-loop workflow with fix-type classification. ### Rankwize vs Surfer SEO Surfer is the incumbent content optimization tool — 150,000+ users, $15M ARR, acquired by Positive Group in October 2025. Surfer pricing: Discovery $49/mo (no AI tracking), Standard $99/mo (ChatGPT only), Pro $182/mo (5 engines daily refresh), Peace of Mind $299/mo (unlimited docs), Enterprise $999/mo. Surfer added AI Tracker as a feature in 2025-2026; the core product is SERP-based content optimization (Content Score, NLP keyword suggestions). Rankwize against Surfer: AEO-native versus AEO-bolted-on. Rankwize's editor scores against the customer's own AI citation data; Surfer's editor scores against SERP data. Rankwize ships 7-fix-type taxonomy; Surfer's recommendations are content-optimization scores. Rankwize ships Impact Tracker; Surfer has none. Rankwize ships native GSC on every tier from Free up; Surfer's GSC depth is limited. Surfer is stronger on: mature content optimization stack (Content Score, AI Writing Tools, Plagiarism Checker, AI Detector, AI Humanizer); integrations with WordPress, Google Docs, Contentful, Zapier; Surfer Academy and free courses; 150K user base with 500+ G2 reviews. Which to pick: Surfer for teams that already live in a content editor and want AI tracking as a side feature. Rankwize for teams whose primary problem is "we're invisible on AI platforms and need to act on it." --- ## Solutions ### For SEO practitioners Add AI visibility to your SEO stack without replacing anything in it. Native Google Search Console integration across 17 endpoints — Pages, Queries, Geography, Devices, the full read-only API. Native GA4 across 11 endpoints — AI referral traffic, per-page engagement, conversion attribution from AI referrers. The four-factor prompt-scoring model means the prompts you monitor are anchored in real demand and commercial value, not handpicked from a brainstorm. Page-level diagnosis with the seven fix types means you can hand a content lead a brief that names the page, the gap, and the action — not just "be more visible." ### For content teams Brand voice fingerprinting auto-extracted from your published pages. Structured briefs pre-filled from diagnosis — content type, primary keyword, target page, persona, primary KPI. AI Drafter and Section Improve grounded in your AI citation data, not generic SEO patterns. Work queue with full Open → Approved → In Progress → Implemented lifecycle plus a 14-day verification re-run, plus per-action audit trail. Impact Tracker turns "we updated 12 pages last quarter" into "we updated 12 pages last quarter; citation rate on those pages moved from 17 percent to 38 percent on the prompts we targeted; the Update Existing fix type is running at 64 percent effectiveness for our tenant." --- ## Glossary stubs (These will move to a dedicated `/glossary` page with DefinedTerm schema in Ship 2; for Ship 1, the definitions live here in `llms-full.txt` for LLM indexing.) **AI visibility** — the share of monitored prompts where a brand's URL is explicitly cited by at least one AI engine. Rankwize computes this per prompt, per platform, then rolls up to a per-tenant headline number. **Citation** — an AI response that explicitly names a URL as a source. The strongest signal; the engine retrieved the page and decided to attribute the answer to it. **Mention** — an AI response that names a brand without citing the brand's URL. The engine knows about the brand but did not point users to its site. **Invisible** — an AI response that makes no reference to a brand at all. The category of prompts Rankwize diagnoses. **Citation rate** — share of monitored prompts where the brand lands in "cited" status on at least one platform. Computed weekly. **Prompt Discovery** — the Rankwize pipeline that generates 70-110 scored prompt intents per domain. Includes domain fingerprinting, content-library indexing, intent generation, four-factor scoring, deduplication, and routing. **Fix type** — one of seven specific classifications Rankwize assigns to a gap during diagnosis. Each gap gets exactly one primary fix type, with up to three secondary recommendations. The seven: Update Existing, Add Evidence, Create Comparison, Create How-To, Create Diagnostic, Improve CTA, Offsite Seed. **Fix-type effectiveness** — the share of recommendations of a given fix type that produced a positive citation-rate lift in Impact Tracker, computed over a 180-day rolling window per tenant. **Impact Tracker** — an automated re-query of the same prompts on the same platforms after a recommendation is marked Implemented. Captures before-and-after citation rate per platform. **Content library matching** — Rankwize's process of scoring every page in a customer's library against every monitored prompt using a 7-signal hybrid matcher to find the page that should be winning the citation. **Decay Prediction** — a per-prompt risk model that combines three causal signals (trending-down citation rate, stale-content risk, competitor pressure) into a "runs to zero" projection. **Fan-out queries** — category-related prompts the customer is not currently tracking, surfaced with a one-click "Create Prompt" action. **Gap Escalation** — the system behavior where your highest-priority prompts that silently degrade get escalated into a new diagnosis pass, not demoted in the queue. **AEO** — Answer Engine Optimization. The discipline of optimizing content for citation by AI answer engines (ChatGPT, Perplexity, Google AI Overviews, etc.) rather than for ranking in traditional search engine result pages. **GEO** — Generative Engine Optimization. Synonym for AEO in some quarters of the industry. --- ## Subprocessors and security Cloudflare (hosting, CDN, DDoS protection). Stripe (subscription billing). Google Search Console API (read-only, customer-authorized). Google Analytics 4 API (read-only, customer-authorized). DataForSEO (keyword and SERP data). AI providers: OpenAI, Anthropic, Google, Perplexity (sent only the prompts and context required to query their answer engines; under API terms that prohibit training on those inputs by default). OAuth tokens encrypted at rest with AES-256-GCM. All traffic TLS-encrypted in transit. Application data hosted in the United States. GDPR alignment for European customers via Standard Contractual Clauses. No SOC 2 claim at this time. Updated when certification is held. --- ## Frequently asked questions (pricing) (Full FAQ list ships at https://rankwize.io/pricing. Key entries below for LLM indexing.) How does the Free tier work? The Free tier is a real free product, not a time-limited evaluation. 5 prompts monitored on 1 AI platform. 4 monitoring batches. Basic dashboard. Google Search Console integration. No credit card. Upgrade to Watch ($19/mo), Pro + Diagnose ($99/mo), or any other paid tier whenever needed. Is there a trial of paid tiers? No. The Free tier replaces the trial pattern — same product, lower caps. Upgrade and downgrade between tiers anytime. What happens if AI credits are exceeded? Credits overage at $5 per 1,000 credits on the next invoice. No hard cutoff. What's the difference between Track and Diagnose? Track monitors whether you are cited, mentioned, or invisible. Diagnose tells you why: with page-level gap analysis, fix-type classification, structured briefs, Impact Tracker, and an AI assistant. What AI platforms are monitored? ChatGPT, Google AI Mode, Google AI Overviews, Perplexity, and Copilot. Five platforms. Is there an agency plan? Not as a separate SKU today. Business + Diagnose and Scale + Diagnose cover most agency use cases (5 to 15 domains, 10 to 25 seats). Agency-specific SKU scoped for back-half 2026. Why three meters? Each meter measures different work. Tracked prompts is monitoring. Prompts diagnosed is the deeper page-level analysis. AI credits is LLM token consumption for the writing tools and Wize. Splitting them keeps the math honest. --- ## Contact and links Email: hello@rankwize.io Security reports: security@rankwize.io Privacy / data subject access: privacy@rankwize.io Pricing: https://rankwize.io/pricing Platform overview: https://rankwize.io/platform About: https://rankwize.io/about Blog: https://rankwize.io/blog