Technical SEO work identifies delivery problems that prevent your important pages from being reached, interpreted or used as intended. TANTU AI connects reproducible findings to the affected templates and buyer journeys, then defines an implementation and verification path. The review separates what a server returns, what a browser renders and what authorized production evidence can establish. This helps your developers fix the actual defect and understand the limits of the test. It does not turn a local check or successful deployment into proof of indexing or an AI citation.
Investigate the failure before prescribing the fix
| Question | Evidence to inspect | Why it matters |
|---|---|---|
| Can the page be reached? | HTTP response, access controls and crawl rules | A blocked or failed page needs an access fix. |
| Is this the intended version? | Canonical, redirects and duplicate URL patterns | Conflicting versions dilute the intended page architecture. |
| Is key information readable? | Returned HTML, headings and page content | Important facts should not depend on a visual screenshot. |
| Can visitors act? | Links, mobile layout and form behavior | Discovery has limited value if the buying path fails. |
We begin with a representative sample of templates and high-value pages. A pricing page, product detail and editorial article may expose different problems; testing one homepage cannot establish the condition of the whole site.
Keep a full SEO audit distinct from an AI diagnostic
The $990 AI search diagnostic focuses on an agreed question sample, brand evidence and priority gaps. It is not an unlimited crawl audit, migration plan or engineering engagement. A standalone SEO audit is quoted after the page inventory, platforms and required depth are understood.
An audit output should include the affected URL or template, the observed behavior, business impact, proposed fix, implementation owner and acceptance check. Lists of generic recommendations without reproducible evidence are difficult to prioritize.
Describe facts already visible to the visitor
We use structured data for genuine entities and page types: the operating organization, its contact details, articles, services and breadcrumbs. The markup must agree with the page. See Google Search Central: Structured data.
We do not invent reviews, ratings, branches, certifications or performance claims for markup. An Organization address identifies the actual operator; it does not create a local presence in a target market. No special AI schema is required to buy a visibility service.
Make the release review concrete
- Confirm successful responses for the intended canonical pages and a genuine 404 for unknown paths.
- Keep internal links pointed at the preferred URLs and remove broken destinations.
- Check the XML sitemap against the indexable canonical inventory.
- Keep preview and restricted environments out of public indexing.
- Review redirects without dropping meaningful query parameters.
- Recheck critical forms and links after a template or routing change.
Search Console, Webmaster Tools and actual server logs can add evidence after you authorize the relevant access. A locally generated file cannot establish that a production firewall permits the same request.
Turn the audit into an owned backlog
Prioritize by affected buying journeys and the scale of the template issue. A broken inquiry path may deserve attention before a minor metadata refinement. Group shared defects so the engineering team can repair the underlying template rather than manually changing every page.
Implementation and retesting responsibilities are agreed before work starts. We report what was checked, what changed and what still requires production access. Crawlability, indexing and search performance remain separate stages of evaluation.
Compare the delivered page with the intended page
For a priority URL, inspect the response status and relevant directives, the returned document and the rendered browser view. Compare the important facts, navigation and action links across these records. A browser may display information added later by scripts; a raw response alone may not explain the full user experience. Neither view by itself establishes how a particular external system processed the page.
An illustrative product page could display a price correctly while returning an obsolete description in its initial content. Another could return the correct text but fail to render a working inquiry action. Record the exact discrepancy and affected template before proposing a fix. Where production logs or authorized webmaster evidence are available, use them to investigate actual requests and processing separately. Acceptance should state which behavior was retested, on which environment and with which remaining limitations, rather than declaring the whole site “AI ready.”
Control the release risk of a shared-template repair
A template change can improve many pages and also affect pages that were previously working. Before release, identify the representative page types, expected behavior and critical paths to recheck. Include pages with different content lengths, language variants or parameter behavior when they rely on the same component. The sample should follow the actual change surface, not an arbitrary URL count.
Agree a practical rollback condition for changes affecting routing, canonical output or lead capture. For example, unexpected redirects on priority pages or a broken inquiry submission should stop the release review and trigger the agreed recovery process. After deployment, retain the version, test evidence and unresolved issues so later search changes can be interpreted against a real change log. This approach makes implementation reviewable while keeping development, production access and follow-up monitoring within the separately agreed scope.
Common questions
Will a technical fix guarantee indexing?
No. The fix can remove an identified obstacle. Search engines still decide which pages to crawl, index and serve.
Do you install an automatic ranking plugin?
No. We scope evidence-based website work. Tools may assist the review, but they do not replace the diagnosis or create guaranteed placements.
Sources & method
Platform facts are linked below. The planning steps, examples and acceptance criteria are TANTU AI’s operating approach. Examples are illustrative unless identified otherwise.
Reviewed 16 September 2026. Product availability and controls can change.