Fintech / alternative investing

Rebuilding Search and Wikipedia Accuracy for an Investment Platform

Paired reputation and Wikipedia work for an accredited-investor platform, carrying the corrections through to the Knowledge Panel and to what AI assistants told prospective investors.

100% Correct Outcome (change in inaccurate/outdated coverage)
3 Weeks Time to first confirmed edit or correction
11 Months Total engagement duration

Impact at a Glance

Wikipedia article accuracy

Before Outdated, unsourced
After Neutral refs, facts updated

Google Knowledge Panel

Before Mirrored the article
After Aligned across all sources

AI assistant answers

Before Repeated old claims
After Corrected in 12 weeks

The Challenge

An alternative-investment platform for accredited investors was dealing with two connected problems: general search results skewed toward complaint sites and old news coverage of a since-resolved regulatory matter, and its Wikipedia article compounded the problem by presenting that matter without the resolution or context. For a platform whose whole pitch depends on investor trust, a prospective investor searching the company - or asking an AI assistant whether the platform was trustworthy - was getting a one-sided, outdated picture. The two problems needed to be solved together: search-result work alone would not fix what Wikipedia said, and Wikipedia work alone would not address the surrounding search landscape feeding the same narrative into AI assistant answers.

Our Solution

Paired reputation and Wikipedia work for an accredited-investor platform, carrying the corrections through to the Knowledge Panel and to what AI assistants told prospective investors.

  1. Regulatory-History Rewrite

    Read the article against Wikipedia's sourcing and notability standards, then rewrote the founding, leadership and regulatory-history sections from independent reporting so the resolved matter appeared with its resolution attached.

  2. Third-Party Editor Handoff

    Passed the sourced corrections to Reputation X's independent editor network, who judged the route themselves — a direct edit, a Talk-page proposal, or advance notice to editors already watching the page.

  3. Database and Wikidata Alignment

    Traced which panel fields came from the article and which from linked Wikidata items, then filed corrections through both so the panel stopped contradicting the rewritten page.

  4. Investor-Query Answer Tracking

    Put the questions an investor would actually ask to ChatGPT, Gemini, Perplexity and AI Overviews on a repeating schedule, watching for answers still leaning on the superseded account.

  5. Search Landscape Repair

    Ran reputation work alongside the article so the results surrounding it told the same current story, rather than leaving a corrected page marooned in stale coverage.

The Results

Engagement milestones are listed below.

Day 14

Audit closed. Priority inaccuracies ranked across the article, the panel and assistant answers.

Month 1–2

First sourced edits went to volunteer editors; panel and Wikidata corrections filed in parallel.

Month 3–4

Rewritten sections holding. Panel now aligned across databases, Wikidata and the article.

Month 6+

Most assistant answers had picked up the corrections within twelve weeks of the approved edits; monitoring continues.

Key Takeaways

  • Search work and Wikipedia work fail separately. The article feeds the results and the results feed the article, so correcting one alone leaves the other pulling against it.
  • A resolved regulatory matter reads as an unresolved one whenever the resolution is missing. The fix is context, not deletion.
  • Panel fields come from several places at once — the article, Wikidata, linked databases. Correcting only the article leaves the panel wrong.
  • Assistant answers lag the edit that fixes them. Budget weeks, not days, and keep checking.

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