Integrus Mortgage Appears in 0.0% of AI Answers. Here's Our Five-Step Plan to Improve Its AI Visibility.

Mark HuntleyBy Mark HuntleyFounder and CEO
9 minutes read

Key Takeaways

  • Integrus Mortgage had 0 mentions and 0 recommendations across the benchmarked AI answers.
  • The first priority is a verified baseline scorecard and a scoped fact-review list.
  • Website and third-party page changes should wait until claims are confirmed against primary sources.
  • Buyer-question content should be created only after existing coverage is checked and a real gap is found.

Answer Capsule

In November 2026, Integrus Mortgage appeared in 0 of 709 AI answers included in the Residential Mortgage Brokerage benchmark (0.00%). It received 0 recommendations (0.00%), with 0 Top 3 placements and 0 first-place recommendations. A mention means the company appeared in an answer; a recommendation means the answer affirmatively endorsed it.

Our plan compares the company with its competitors, checks conflicting AI claims against reliable sources, and identifies website pages, third-party sources and buyer questions to address. The historical results show how the figures changed across available months. Different monthly samples limit those comparisons, and conflicting AI claims require verification before corrections are proposed.

Current AI visibility

Questions This Section Answers

  • How do Integrus Mortgage mentions, recommendations and placements compare with its Residential Mortgage Brokerage peers?

Integrus Mortgage recorded 0 mentions (0.00%) and 0 recommendations (0.00%) across 709 answers included in the benchmark. Top 3 placements numbered 0; first-place recommendations numbered 0. Framing among its mentions was 0 positive, 0 neutral and 0 negative.

Rank

Company

Mentions

Mention rate

Recommendations

Recommendation rate

Top 3

Top 3 rate

#1

#1 rate

1

Rocket Mortgage

616

86.88%

366

51.62%

298

42.03%

186

26.23%

2

Bank of America

549

77.43%

292

41.18%

185

26.09%

61

8.60%

3

Navy Federal Credit Union

497

70.10%

290

40.90%

176

24.82%

49

6.91%

4

Better Mortgage

220

31.03%

130

18.34%

82

11.57%

20

2.82%

5

CrossCountry Mortgage

261

36.81%

112

15.80%

69

9.73%

11

1.55%

6

United Wholesale Mortgage (UWM)

238

33.57%

92

12.98%

61

8.60%

29

4.09%

7

Cohen Financial Group

4

0.56%

2

0.28%

2

0.28%

1

0.14%

7

Loan Factory

6

0.85%

2

0.28%

2

0.28%

0

0.00%

9

C2 Financial Corporation

4

0.56%

1

0.14%

1

0.14%

1

0.14%

10

Avenir Mortgage Planners

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Bridgepoint Funding

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

California Mortgage Advisors

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Insignia Mortgage

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Integrus Mortgage

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

JVM Lending

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Mares Mortgage

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Resource Home Loan

0

0.00%

0

0.00%

0

0.00%

0

0.00%

10

Sammamish Mortgage

1

0.14%

0

0.00%

0

0.00%

0

0.00%

10

The Loan Story

0

0.00%

0

0.00%

0

0.00%

0

0.00%

Integrus Mortgage does not appear in the recorded answers at all, so there is no recommendation base to improve yet. The practical goal is to get the company into answers accurately before chasing placement. A first target should be a small, verifiable presence rather than a rate comparable to the large national lenders at the top of the table.

That absence also means there is no framing to assess. With no mentions, positive, neutral and negative wording cannot be read as a signal of how the company is described. The agency would treat this as a clean starting point and build a baseline scorecard that records where the company is named, in what context, and whether the wording is accurate.

What changed since last month

Questions This Section Answers

  • How did Integrus Mortgage counts and coverage differ across the available monthly snapshots?

Metric

Oct 2026

Nov 2026

Mentions

0 / 120 (0.00%)

0 / 709 (0.00%)

Recommendations

0 / 120 (0.00%)

0 / 709 (0.00%)

Top 3 recommendations

0 / 120 (0.00%)

0 / 709 (0.00%)

#1 recommendations

0 / 120 (0.00%)

0 / 709 (0.00%)

From October 2026 to November 2026, Integrus Mortgage's mention count stayed at 0, while its recommendation count stayed at 0. The recommendation rate was 0.00% and 0.00% respectively.

The recorded result is unchanged between the two selected months: no mentions and no recommendations in either sample. That flat line is the finding, and it is worth stating plainly rather than dressing up as momentum.

The two months used different answer samples, so the comparison shows only that the recorded outcome held steady. It does not explain why the counts stayed at zero, and the larger November sample should not be read as evidence of anything beyond broader coverage. The agency would keep the baseline scorecard consistent so future months can be compared on the same footing.

AI recommendation trend

Observed recommendation rate (%), Oct 2026 to Nov 2026

  • Integrus Mortgageno change
    Oct 20260.00%
    Nov 20260.00%

Separate selected monthly samples. Missing points are unavailable, not zero. Provider/prompt equivalence is unverified; rate movement does not demonstrate causation.

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Step 1. Measure

Questions This Section Answers

  • What should the agency measure and verify first for Integrus Mortgage?

AI answers contained 0 conflicting claims about Integrus Mortgage: 0 critical, 0 high, 0 medium, 0 low. Of these, 0 were rated critical or high priority; the critical claims are included in that total. These ratings help prioritize fact-checking. They do not establish that a company or publisher made an error.

A visibility comparison would show the client where it stands against named competitors and where the gap is widest, without implying that closing it is quick. Pairing that with a list of claims to fact-check gives a second, separate workstream: confirming what is actually true about the company before any content is written.

The fact-check list should be built from current primary sources, with each item assigned an owner and a review status. Ratings help order the work; they do not establish that the company or a publisher made an error. The agency would deliver the scorecard and the scoped review list as the first concrete outputs.

Step 2. Make the website consistent

Questions This Section Answers

  • Which recorded claim differences about Integrus Mortgage should be verified before proposed page edits?

No results are available for this part of the analysis.

Both columns quote AI answers, not verified company facts. Resolve the entity, date and source before deciding whether a correction is warranted; different dates can explain an apparent conflict.

No disputed topics were supplied for this part of the analysis, so there is nothing to verify or correct at this stage. The agency would not invent conflicts to fill the gap.

Where claims do surface later, the first step is to resolve the entity, the date and the source before deciding whether a correction is warranted. Different dates can explain an apparent conflict, and an ambiguous company match stays outside the correction queue. Page briefs would be drafted only after approved facts are confirmed.

Step 3. Align the external narrative

Questions This Section Answers

  • Which cited third-party pages are relevant to fact review for Integrus Mortgage?

No results are available for this part of the analysis.

These pages were selected because they relate to the company in the captured answers. Their current contents still need checking before any correction request. A page linked to a conflicting claim is not necessarily its cause, and the same answer may contribute to more than one row.

No source pages were supplied for review, so the external work starts with building a shortlist rather than making requests. The agency would identify pages that actually discuss the company and check their current contents before proposing any change.

A page linked to a conflicting claim is not necessarily its cause, and a citation does not show that a source influenced an answer. Requests to publishers would be evidence-backed and framed as corrections only where primary sources support them. Responses and no-change decisions would be logged separately from confirmed edits.

Step 4. Optimize priority company pages

Questions This Section Answers

  • Which observed Integrus Mortgage website pages should receive review briefs?

No results are available for this part of the analysis.

The company's website was cited 0 times across 0 distinct page addresses; the table shows 0 pages selected for review. Zeros in the answer columns mean no matching answers were recorded. A cited page is not automatically a page that accompanied a recommendation.

No company pages were cited in the recorded answers, so the page work begins with a shortlist rather than a rewrite. The agency would confirm which pages exist, what they currently say, and which approved facts they should carry.

Page briefs would be built around verified company facts and the questions buyers actually ask, with each brief tied to a specific page. A cited page is not automatically one that accompanied a recommendation, so page work is judged on accuracy and usefulness first.

Step 5. Publish around buyer questions

Questions This Section Answers

  • Which observed buyer questions support content briefs for Integrus Mortgage?

No results are available for this part of the analysis.

These are recorded answer observations, not search volume, verified demand, or proof of missing website content.

No buyer questions were supplied for this part of the analysis, so content briefs cannot yet be tied to observed questions. The agency would start by recording the questions that appear in answers and checking whether the website already covers them.

Recorded answer observations are not search volume or proof of missing content. Where a genuine gap is confirmed, a brief would set out the question, the approved answer and the supporting evidence, and existing coverage would be checked before any new page is proposed.

Our 90-day action plan

Questions This Section Answers

  • How should the agency sequence the proposed Integrus Mortgage work and judge completion?

Period

Deliverable

Completion criterion

Days 1–30

Baseline scorecard, scoped fact-review register and page/source shortlist

Each record has an owner, evidence requirement and review status

Days 31–60

Approved page briefs and justified publisher requests

Separate confirmed edits, no-change decisions, requests and responses

Days 61–90

Buyer-content briefs and a fresh scorecard

Record work completed separately from measured answer outcomes and comparability limits

The first month produces the baseline scorecard, a scoped fact-review list and a page and source shortlist, each with an owner and a review status. This establishes what is known before any content or outreach begins.

The second month turns confirmed facts into approved page briefs and justified publisher requests, with confirmed edits, no-change decisions, requests and responses recorded separately. The third month adds buyer-content briefs and a fresh scorecard. Completed work is reported apart from measured answer outcomes, and no visibility gain is promised.

Methodology

Questions This Section Answers

  • How are Integrus Mortgage answer metrics and citation populations defined?

This report covers 2026-11. The exact dates when the original AI answers were collected have not been verified. The visibility rates use 709 answers that met the benchmark's inclusion rules. A company is recommended only when the answer both endorses it and uses positive wording. Top 3 and first-place counts are part of those recommendations, not extra recommendations.

An answer can mention or recommend several companies, so company counts cannot be added to find the number of distinct answers. The net sentiment score is positive minus negative mentions, divided by all company mentions; it describes answer wording, not customer satisfaction.

The wider citation analysis covers 800 captured answers and 4745 appearances of cited URLs. Citation appearances across all captured answers differ from the number of benchmark answers citing a page and the number that also recommend a company. The current contents of cited pages and disputed company claims still need independent verification.

Monthly sample coverage:

Reporting month

Answers included

AI services covered

Services

Oct 2026

120

8

ChatGPT, claude, deepseek, Gemini, Google AI Mode, Google AI Overviews, grok, Perplexity

Nov 2026

709

6

ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity

The answer samples differ between months. These comparisons show how the recorded results changed; they do not establish why they changed.

The report covers a single month, and the exact dates the answers were collected have not been verified. A company counts as recommended only when an answer endorses it with positive wording; placement counts sit inside recommendations rather than adding to them.

Answers can name several companies, so company counts cannot be summed into a number of distinct answers. The two monthly samples differ in size and service coverage, so comparisons show what was recorded, not why it changed. Cited pages and disputed claims still need independent verification.

Our first three priorities

The first priority is to establish an accurate baseline: a scorecard that records where Integrus Mortgage is named and how, built from verified facts rather than assumptions. With no recorded mentions, accuracy matters more than volume at this stage.

The second is a scoped fact-review list and a shortlist of pages and sources worth checking, each with an owner and evidence requirement. Ambiguous matches stay out of the correction queue until the entity is confirmed.

The third is buyer-question content built only where existing coverage has been checked and a real gap confirmed. These are proposed work items; none of them guarantees a change in measured visibility.

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Understanding AI search visibility.

AI search experiences create answers by pulling information from many places online and summarizing it into a single response.

What Is AI Citation Intelligence?
AI citation intelligence is the process of measuring where AI platforms source their information and how frequently a brand is mentioned or referenced in AI-generated responses. Because LLMs synthesize across multiple sources, the sites and brands that appear repeatedly tend to influence how a topic or company is framed. This practice focuses on identifying which sources shape AI outputs and tracking brand visibility across different AI systems.
What Is Citation Architecture?
Citation architecture describes the set of sources that consistently inform how AI systems talk about a brand, product, or topic. LLMs draw from websites, articles, forums, and public discussion, and the sources they rely on most often become the backbone of their answers. Building strong citation architecture means ensuring that accurate, credible, high authority sources are the ones most likely to shape the way AI tools summarize and recommend a brand.
What Is Generative Engine Optimization?
Generative engine optimization (GEO) is the practice of improving the chances that AI systems use and cite your brand or content when generating answers. While traditional SEO is centered on ranking pages in search results, GEO focuses on how LLMs retrieve, interpret, and combine information when responding to a question. The objective is to strengthen the content and sources AI systems rely on, so your brand is treated as a trusted reference in AI responses.
What Is AI Share of Voice?
AI share of voice tracks how often a brand appears in AI-generated answers compared with competitors in the same category. It reflects visibility across AI platforms such as ChatGPT, Gemini, Claude, and Perplexity. Monitoring AI share of voice helps organizations see whether AI systems consistently include and recommend their brand for key queries or whether competitor brands are showing up more often.

About The Author

Mark Huntley

Mark Huntley

Founder and CEO

Mark Huntley, J.D. is founder of CiteWorks Studio, a strategic advisory focused on visibility, authority, and recommendation presence in AI-shaped search environments. His work centers on embedding-level GEO, vector optimization, and cosine gap engineering — helping brands align their digital presence with the retrieval systems that increasingly shape discovery, interpretation, and choice.

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