A Google AI Overview once answered “no” when people asked whether Feature Upvote had a public REST API. For a small B2B SaaS vendor, that one line of incorrect AI copy cost visibility for an integration-led buyer — and potentially revenue. The company fixed it within days by treating the problem as a content-and-indexing issue rather than a mysterious AI failure.

What happened and why it matters

Feature Upvote launched a public REST API in July 2026. Despite new documentation and an announcement, Google’s AI Overview cited older blog posts that said the platform did not have an API, and returned the wrong answer to queries. The mismatch meant searchers could be deterred before they ever reached Feature Upvote’s site.

The case matters because AI-generated summaries are becoming a front door for many buyers. When those summaries rely on stale sources, they can short-circuit discovery and damage conversion. The fix—update the authoritative source material and get it indexed—was simple, repeatable, and fast.

How Feature Upvote corrected Google’s AI Overview

After publishing the API announcement on July 24, the team identified outdated pages and took three concrete steps:

  • Updated site pages that contained outdated statements suggesting there was no API.
  • Published clear, standalone documentation and help pages that stated the fact plainly (for example: “Yes, Feature Upvote has a public REST API”).
  • Used Google Search Console’s URL Inspection tool to request indexing of the updated and new pages.

Within an hour of submitting URLs for indexing on July 28, some AI Overview queries flipped to “Yes.” Consistency improved over the following days, though answer variations persisted depending on how queries were phrased. By September 10 the Overview returned the correct fact for at least one prompt, but cited different internal pages — a reminder that AI answers and their citations can change as indexing and answer-extraction systems re-evaluate sources.

Step-by-step checklist to fix incorrect AI answers about your brand

Apply this sequence when an AI search platform reports an incorrect brand fact:

  1. Prioritize the facts that matter. Track brand facts that directly affect conversion: feature availability, pricing, refund policy, operating areas, compliance, and hours.
  2. Identify which AI platforms matter to your audience. Use analytics tools to see where your organic traffic comes from; if Google delivers most visitors, start with Google’s AI Overviews.
  3. Establish a baseline. Run a small set of consistent prompts that target each fact (three to five variants per fact). Record the exact answers and the pages the AI cites. Screenshot and timestamp results so you can measure changes objectively.
  4. Debug the information supply chain. For any incorrect answer, trace back to the specific pages the AI used. Check whether those pages are outdated, ambiguous, or not in your canonical site structure. Publish a dedicated page or FAQ that states the fact plainly near the top in natural search language (e.g., “Yes, [Product] has a public REST API”).
  5. Force reindexing. Request indexing via Google Search Console (URL Inspection). For other platforms, follow their submission or webmaster flows if available. Re-run your prompts after submitting and log changes.
  6. Reinforce authoritative signals. Where feasible, fix third-party listings, correct partner references, or secure corroborating pages. In many cases, updating and reindexing your own authoritative pages produces the fastest improvement.

Practical cautions and expected behavior

Two caveats from the Feature Upvote case are instructive. First, fixes are not always instantaneous or permanent: AI answers can revert or change as systems re-index and re-score sources. Second, AI answers can vary by query phrasing; a correct answer for one prompt may still be wrong for a paraphrased question. Monitoring diverse prompt formulations is essential.

What teams should do next

Turn this process into a routine part of product launches and content updates. Add these steps to your release checklist: publish a clear, standalone page for any factual claim that affects buying decisions; submit the page for indexing; and schedule follow-up checks on your set of test prompts. Log which pages AI platforms cite and how long it takes for answers to update.

For teams that depend on search-driven acquisition, brand-fact management is now both a content and an indexing discipline. Treat incorrect AI answers as a correctable mismatch between authoritative content and the search index — not as an unsolvable hallucination.