--- optiview_delivery: edge_optimized content_type: semantic_markdown source_url: https://optiview.ai/resources/ai-readable-publishing-vendor-evaluation/ brand_content: included publication_version: "9.0" published_at: 2026-10-16T20:36:07Z composition_version: composition-v2.1.0 presentation_version: presentation-v1.2.3 brand_content_source: narrative_graph delivery_publication: graph:33 narrative_versions: - 33 narrative_version: 33 --- # AI-Readable Publishing Vendor Evaluation: 30 Questions to Ask Buying guide — October 30, 2026 A product promising AI-readable content should be evaluated on what it actually publishes, who controls it and how its behavior can be verified—not simply on the formats it advertises. By Optiview · Sources checked October 30, 2026 [Download this article (.md)](https://optiview.ai/resources/ai-readable-publishing-vendor-evaluation.md) Vendors approach AI-readable publishing through different architectures. Some extend existing website platforms. Others provide transformation, custom interfaces or dedicated publication workflows. A checklist makes those differences easier to assess without assuming that every vendor provides the same feature set. The following 30 questions are an original procurement worksheet. They are not a completed vendor audit, compliance certification or assertion that a particular product passes every requirement. Request written answers, current documentation and demonstrations using a public page you control. Record each response as Verified, Partially Verified, Unsupported, Not Applicable or Unknown. If a feature is not mentioned in documentation, ask the vendor rather than claiming it is absent. ## Questions 1–5: Source content and preparation * 1\. Which website platforms, content systems and response types can your solution process? * 2\. How does it distinguish meaningful page content from navigation, interface text and repeated boilerplate? * 3\. What happens when required information depends on client-side rendering or authentication? * 4\. Can we inspect the exact prepared output before allowing it to become public? * 5\. How are material omissions, source changes and unsupported content types reported? Ask for a demonstration using your own representative page. Do not accept a polished sample from another website as sufficient evidence that the solution handles your source correctly. ## Questions 6–10: Representation and delivery * 6\. Which output formats are supported, and what determines which representation a request receives? * 7\. Which HTTP status, Content-Type, Vary and cache behaviors are documented? * 8\. How are original facts, qualifications, links and structured annotations preserved? * 9\. What fallback behavior occurs when preparation or delivery fails? * 10\. Can we independently test actual public responses without using a vendor dashboard? The [HTTP Semantics specification](https://www.rfc-editor.org/rfc/rfc9110.html) provides useful reference definitions for representation negotiation and metadata. Compare observed behavior with each vendor's documented contract. ## Questions 11–15: Content and publication governance * 11\. Can the organization add approved contextual information beyond existing page content? * 12\. How are drafts distinguished from material that has actually been published? * 13\. Who can approve, publish, revise or withdraw content, and how are those permissions enforced? * 14\. Can reviewers identify the exact content and evidence associated with an approval? * 15\. How does the system handle page-specific information that differs from company-wide context? Optiview's [Publish setup guide](https://optiview.ai/docs/setup/) documents its specific draft, source review, scope and publication controls. Other products should be assessed against their own current documentation rather than presumed to behave identically. ## Questions 16–20: Implementation and website compatibility * 16\. What DNS, proxy, edge, API, CMS or application changes are required? * 17\. Can the existing human-facing website and its navigation remain unchanged? * 18\. What are the documented content-size, runtime, platform or traffic limitations? * 19\. How are canonical URLs, redirects, internal links and existing SEO settings preserved? * 20\. What dependencies must the customer maintain after the initial installation? Request a written architecture diagram and deployment responsibility list. A technically possible integration is not the same as a documented, supported connection. ## Questions 21–25: Security, control and reliability * 21\. What customer data, credentials and website material does the service receive or retain? * 22\. How are account access, permissions and publication authority managed? * 23\. Which security controls and independent assurance documents are available for verification? * 24\. How are deployment failures, unexpected content changes and service interruptions handled? * 25\. What tested options exist for disabling, correcting or restoring publication? The [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) offers voluntary risk-management principles. Using this questionnaire does not establish compliance with NIST, privacy law or any other regulatory framework. Security and legal specialists should evaluate applicable obligations. ## Questions 26–30: Measurement, evidence and ongoing operations * 26\. What evidence proves that an approved representation was actually delivered? * 27\. How does the vendor distinguish delivery, verified crawler activity, retrieval, indexing and citations? * 28\. Which performance claims are supported by controlled studies, and what limitations were reported? * 29\. What operational logs, exports and troubleshooting information can customers access? * 30\. What responsibilities, support commitments and recurring maintenance remain after launch? A vendor may offer strong technical delivery capabilities without evidence of increased AI citation frequency. That is not necessarily a defect; it is an important distinction to preserve during evaluation. ## Turn the answers into a selection memo 1. Mark each question Essential, Preferred or Informational before approaching vendors. 2. Collect vendor responses and current documentary evidence. 3. Demonstrate essential capabilities on a representative public page. 4. Record unsupported claims, unknowns, exclusions and operating dependencies. 5. Select based on verified requirement fit rather than the total number of advertised features. The finished work product is a 30-question evaluation matrix with evidence links, responsible reviewers, unresolved questions and a documented selection rationale. Use the [publishing architecture decision guide](https://optiview.ai/resources/choose-ai-readable-publishing-approach/) before narrowing the candidate approaches. ## Additional source context A defensible buying decision connects documented capabilities to real requirements, operational responsibility and reproducible acceptance evidence. No single feature automatically guarantees AI discovery or citation. Make your brand easier for AI to understand. ### Explore [Website publishing](https://optiview.ai/products/publish/) · [Developer tools](https://optiview.ai/products/#developers) · [Pricing](https://optiview.ai/pricing/) ### Learn [Guides](https://optiview.ai/resources/) · [Developer docs](https://optiview.ai/developers/) · [Research](https://optiview.ai/proof/) · [FAQ](https://optiview.ai/faq/) ### Company [About Optiview](https://optiview.ai/about/) · [Agencies](https://optiview.ai/partners/) · [Contact](https://optiview.ai/#contact) · [Privacy](https://optiview.ai/privacy/) · [Billing terms](https://optiview.ai/billing-policy/) ## Additional page links - [Resources](https://optiview.ai/resources/) - [The AI-readable web](https://optiview.ai/resources/topics/ai-readable-web/) - [AI doesn’t have one view of your website.](https://optiview.ai/resources/what-ai-services-see/) — Continue reading - [Keep the meaning. Simplify the format.](https://optiview.ai/resources/html-versus-markdown-for-ai/) — Continue reading - [The AI-Readable Website Audit: 25 Checks Before You Optimize](https://optiview.ai/resources/ai-readable-website-audit-checklist/) — Continue reading - [Preview a page](https://optiview.ai/demo/) — Continue reading - [Read the setup guide](https://optiview.ai/docs/setup/) — Continue reading --- # Published brand narrative # Site-wide brand information ## Who we are ### Optiview — Parse, Retrieve and Publish for AI Optiview helps businesses and developers make website information easier for AI to use. Parse converts supplied HTML into clean Markdown and source metadata. Retrieve fetches an eligible public HTTPS webpage and prepares its content. Publish helps a verified business prepare its own website content and make approved Narrative Graph context available through a supported connection. Parse and Retrieve use application keys and a prepaid developer wallet. Publish has separate website setup, ownership checks and a subscription. Optiview does not control whether an outside AI service discovers, uses or cites the resulting content. Applies to: Optiview ## Why we matter ### A clearer source, from website content to business context Webpages mix useful information with navigation, layout and application code. Businesses may also have important qualifications, answers and context that are not clearly published. Optiview gives developers a way to prepare source content for their applications, and gives businesses a way to publish the context their teams approve. Your application chooses how to use Parse and Retrieve results. Your business controls what it publishes through Publish. Clearer publishing makes information available; it does not determine an AI system’s answer. Each outside service chooses its own retrieval, recommendations and citations. ## What we offer ### Three products, with separate jobs and clear pricing - **Optiview Parse:** Supply complete HTML and a source URL. Receive clean Markdown, source and output hashes, parser details and processing warnings. Parse does not fetch the URL or execute JavaScript. A successful page uses 1 credit. - **Optiview Retrieve:** Supply one eligible public HTTPS URL. Optiview checks supported access and publisher policies, fetches anonymous static HTML and parses it. It does not search the web, execute JavaScript, bypass a login or access private networks. A successful page uses 5 credits total, including parsing. - **Developer credits:** USD $20 buys 20,000 credits shared by Parse and Retrieve. There is no developer subscription, automatic recharge or scheduled credit expiration. Failed jobs consume no credits. Applicable taxes and the total appear at checkout. Source size, quotas and retention limits apply. - **Optiview Publish:** USD $99 per website per month plus applicable tax. Connect a verified website, review the prepared source and optionally maintain approved Narrative Graph context in Identity, Story, Offerings, Trust, Knowledge and Actions. Choose site-wide or exact-page scope. Saving drafts does not publish them. Eligible AI tools can receive prepared Markdown or HTML through supported delivery, while ordinary visitors keep the normal website. Developer credits do not purchase Publish subscriptions. Parse and Retrieve do not add a customer’s private Narrative Graph to arbitrary third-party pages. See https://optiview.ai/pricing/ and https://optiview.ai/developers/ for the current offer and limits. ## Why trust us ### Inspect the output and understand what the evidence establishes Developers can inspect the prepared Markdown, job status, source metadata, processing warnings and credit ledger. Retrieve records the public source response it observed; Parse identifies supplied HTML rather than claiming to verify the current origin. Publish administrators can review parser output, the combined published-output preview, source checks and publication history. A preview is separate from a recorded live delivery. Saved edits remain separate from the active publication until explicitly published. Our experiment pages contain selected first-party AI conversations and source comparisons. Delivery records establish what was served, not downstream ingestion, recommendations, citations or revenue. Observed language matches do not establish causation or a consistent visibility improvement. Explore the evidence and limitations at https://optiview.ai/proof/. ## Helpful knowledge ### Common questions about the three products **Which product should I use?** Use Parse when you already have HTML. Use Retrieve when you need Optiview to fetch one eligible public page first. Use Publish when your business wants to prepare its verified website and publish approved context. **Do Parse and Retrieve require website ownership or DNS changes?** No website connection is needed for these developer products. You remain responsible for source rights and permitted downstream use. Public availability does not grant a reuse license. **How do developer accounts and keys work?** Create a developer workspace and save the personal sign-in key and offline recovery code. Create scoped service keys for server-side applications. Email is an unverified contact identifier, not account-ownership proof or an email-only recovery method. Keep all credentials private. **Can my agent use Optiview?** The authenticated developer API returns prepared content for your application or model. A downloadable JavaScript client and local MCP adapter are available. Your host must authorize sources and any credit expenditure. Compatibility does not establish adoption or a partnership with an AI provider. **Does the API include my private Narrative Graph?** Parse and Retrieve are source-only. Verified website publishing and approved publisher context belong to the separate Publish workflow. **Does Publish replace our website or CMS?** No. Your website stays in its existing system. Your web team establishes and tests a supported connection. Your team reviews and explicitly publishes any Narrative Graph additions. Ordinary visitors retain the normal website experience. **Does every AI tool get the prepared version?** No. Delivery depends on the website connection, source eligibility and the request. Some tools explicitly request Markdown; supported AI requests may also receive prepared Markdown or HTML through eligible delivery paths. Traditional search crawlers retain the original website response. A claimed tool name does not prove the requester’s identity. **Does the demo publish or save to our workspace?** No. The public demo is a separate preview. Its AI-generated examples require review and do not transfer automatically into an approved publication. **Will Optiview guarantee citations or recommendations?** No. Optiview prepares and publishes sources. Outside AI services choose what to retrieve, use and cite. ## What to do next ### Choose your starting point - [Compare Parse, Retrieve and Publish](https://optiview.ai/products/) to choose the right workflow. - [Create a developer workspace](https://app.optiview.ai/developers) for self-service Parse and Retrieve, then add credits and create an application key. - [Read the API quickstart and agent-tool setup](https://optiview.ai/developers/) for request examples, supported sources, errors, quotas and downloads. - [Review pricing and terms](https://optiview.ai/pricing/) for prepaid credits and the separate Publish plan. - [Preview your website](https://optiview.ai/demo/) to inspect prepared content and explore unapproved narrative examples without connecting or publishing. - [Plan Publish setup](https://optiview.ai/onboarding/) with your web team. Publishing requires ownership checks, review and a supported connection; contact [hello@optiview.ai](mailto:hello@optiview.ai) for assisted setup. Already using Publish? Review your Narrative Graph, publish approved changes explicitly, inspect the combined source in Markdown and check recorded delivery in Activity. Keep your existing visibility tools to study downstream AI answers.