---
optiview_delivery: edge_optimized
content_type: semantic_markdown
source_url: https://optiview.ai/resources/ai-answer-accuracy-evaluation-rubric/
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
---

[Resources](https://optiview.ai/resources/) [Research and evaluation](https://optiview.ai/resources/topics/research-methods/)

Evaluation guide — October 30, 2026

# An Evaluation Rubric for AI Answers About a Business

An AI answer can sound persuasive while omitting the one condition that matters. A useful evaluation must score what is correct, what is missing and what should never have been asserted.

By Optiview · Sources checked October 30, 2026

[Download this article (.md)](https://optiview.ai/resources/ai-answer-accuracy-evaluation-rubric.md)

Evaluating AI answers about businesses requires more than checking whether the brand name appears. An answer might correctly identify a service while inventing a price, overlooking an eligibility restriction or expressing confidence where the available evidence is insufficient.

This rubric provides five scoring dimensions and a separate abstention decision. It is an Optiview-recommended evaluation worksheet, not a validated industry benchmark or a search-ranking metric.

The [NIST AI Risk Management Framework](https://www.nist.gov/itl/ai-risk-management-framework) provides voluntary risk-management principles relevant to evaluating AI systems. Using this worksheet does not establish NIST certification, conformity or endorsement.

## 1\. Establish the approved answer reference

Before scoring, create a reference record containing the question, verified facts, material qualifications, acceptable alternative wording and information the source does not establish.

*   Exact customer question and intended meaning.
*   Required facts supported by authoritative sources.
*   Conditions that materially change the answer.
*   Permissible conclusions and acceptable uncertainty.
*   Forbidden inferences or unsupported claims.
*   Reference revision and review owner.

The reference should be fixed before evaluating responses. Otherwise, reviewers may unconsciously adjust expectations to fit an answer they prefer.

## 2\. Score five dimensions

| Dimension | 0 points | 1 point | 2 points |
| --- | --- | --- | --- |
| Correctness | Material factual error | Mostly correct with minor error | All asserted material facts correct |
| Completeness | Core answer missing | Partially answers question | Required facts included |
| Qualifications | Material restriction misrepresented | Some context omitted | Relevant conditions preserved |
| Supported claims | Material unsupported assertion | Minor unsupported implication | Assertions adequately grounded |
| Clarity | Misleading or unusable | Understandable with ambiguity | Clear and appropriately precise |

The total ranges from zero to ten. This is an internal descriptive score, not a probability of truth. Record individual dimensions because identical totals can conceal very different failure patterns.

Introduce a material-failure flag whenever an incorrect or unsupported statement could materially change a customer's decision. A fluent, comprehensive answer should not pass solely because its aggregate score is high.

## 3\. Evaluate abstention separately

Sometimes the correct answer is that the available information does not establish a conclusion. Abstention should be assessed against evidence sufficiency, not automatically marked as a failure.

| Evidence condition | Appropriate behavior |
| --- | --- |
| Answer established | Provide supported answer |
| Answer partly established | Provide supported portion and identify unknowns |
| Material fact unknown | Avoid guessing; request clarification or say unknown |
| Sources contradict | Identify unresolved conflict instead of choosing arbitrarily |

Record abstention as Appropriate, Unnecessary or Missing. This categorical assessment remains separate from the ten-point score, especially when the entire question cannot be answered responsibly.

## 4\. Score a fictional example

Hypothetical company: Elmbridge Software. Verified fictional reference: its scheduling product supports calendar synchronization only on the Business plan. Illustrative question: 'Does Elmbridge support calendar synchronization?'

Illustrative answer: 'Yes, every Elmbridge plan supports calendar synchronization.' This answer identifies the capability but falsely extends it to every plan.

| Dimension | Illustrative score | Reason |
| --- | --- | --- |
| Correctness | 0 | Incorrect plan coverage |
| Completeness | 1 | Capability identified; qualifying context omitted |
| Qualifications | 0 | Material plan restriction misrepresented |
| Supported claims | 0 | Universal availability unsupported |
| Clarity | 2 | Clear wording, despite factual failure |

Illustrative total: 3/10, with a material-failure flag. This is an invented teaching example, not a real model evaluation or customer observation.

## 5\. Make scoring reproducible

1.  Freeze the reference and rubric before collecting answers.
2.  Retain the complete answer and available citations.
3.  Have reviewers score independently when practical.
4.  Record disagreements and their resolution.
5.  Report dimension scores, material failures and abstention separately.
6.  Preserve the question, source and evaluator context.

Optiview's [published methodology](https://optiview.ai/proof/methodology/) distinguishes observed answers from stronger causal conclusions. This proposed rubric can support future authorized studies without retroactively rescoring or expanding earlier accepted findings.

## Additional source context

Score answers against an approved factual reference, reward appropriate uncertainty and treat materially unsupported assertions as failures regardless of fluency.

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

- [Publishing information doesn’t mean AI receives it.](https://optiview.ai/resources/what-openai-browser-code-taught-us/) — Continue reading
- [How to Design a Reproducible AI Website Retrieval Experiment](https://optiview.ai/resources/ai-retrieval-experiment-design-template/) — Continue reading
- [Does Markdown Improve AI Answer Quality? A Controlled Test Plan](https://optiview.ai/resources/markdown-vs-html-controlled-study-protocol/) — 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.