Document Management Software AI Visibility Ranking Trends - November 2026

Answer capsule

The November 2026 Document Management Software benchmark compares 10 companies across 404 AI answers that met its inclusion rules. Box leads with 96 recommendations (23.76% of answers). At least one tracked company was recommended in 119 answers; some answers recommended several companies.

The rankings distinguish being mentioned from receiving an affirmative recommendation, then examine placement and the wording used about each company. Earlier monthly results show how counts and rates changed, with each month using its own answer total. These results describe the answers reviewed, not product quality or customer satisfaction. Differences between monthly samples limit comparisons and do not establish why a result changed.

For the strategic interpretation of this benchmark, read CiteWorks Studio's analysis of How AI Search Is Recommending Document Management Software

Industry leaderboard

Questions This Section Answers

• How do Document Management Software rank by recorded AI recommendations in November 2026?

The leaderboard orders companies by how many answers recorded an affirmative recommendation, not by how often they appeared. A company can be named frequently yet endorsed rarely, so mention counts and recommendation counts answer different questions.

Ties in recommendation counts would share a rank; near-equal counts should be read as close rather than decisive. Placement figures are nested inside recommendations, so they refine the picture of where endorsements landed rather than adding separate wins.

Key findings

Tracked-company answer coverage

Questions This Section Answers

• How often did the November 2026 Document Management Software answer sample recommend any tracked company?

119 distinct answers recommended at least one tracked company. Counting each company recommendation separately gives 464, because an answer can recommend several companies. Answers with no tracked recommendation may still have recommended companies outside this comparison.

Every included answer named at least one tracked company, but only a minority recorded an affirmative recommendation for any of them. That gap separates presence from endorsement: being named is common, being recommended is not.

Because one answer can recommend several companies, company-level recommendation totals exceed the number of answers containing a recommendation. Answers without a tracked recommendation may still have named companies outside this comparison, so coverage here is bounded by the tracked set.

Reach and affirmative recommendation

Box ranks 1 by recommendation count. Mentions: 338 (83.66%); recommendations: 96 (23.76%). Top 3 placements: 43 (10.64%); first-place placements: 20 (4.95%).

Wording about the company: 105 positive, 230 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 28.4%. The net framing score was 0.30 (defined in Methodology).

242 mentions had no recorded recommendation. Of recorded recommendations, 44.79% were Top 3 and 20.83% were first-place.

Box leads on recommendation count, but its mentions far outnumber its recommendations, and most of its mentions carried neutral wording. Reach and endorsement therefore diverge: appearing in an answer does not imply being put forward.

A tie in recommendation counts would be reported as a tie, not resolved into a unique winner. The recommendation-to-mention ratio describes the recorded answers only; it is not a measure of customers, sales or conversion.

Recommendation order and placement

Top-three and first-place placements are subsets of recommendations, not additional endorsements. A company recommended often may still be placed first rarely, and the printed counts show those two patterns diverging across companies.

Placement shares use the same answer denominator as recommendations, so first-place shares cannot exceed shortlist shares. Ordering within an answer reflects how the recorded response was worded, not a verified product ranking.

Classified framing in context

Framing classifies the wording surrounding each mention as positive, neutral or negative. Neutral wording dominates for most companies, which means many appearances carry no evaluative language either way.

Framing is not customer sentiment or an assessment of company quality, and it does not explain why a recommendation was or was not recorded. A high positive share alongside few recommendations simply describes how those particular answers were phrased.

Company results in detail

Box

Questions This Section Answers

• What do the November 2026 AI answer results show about Box mentions, recommendations and placement?

Box ranks 1 by recommendation count. Mentions: 338 (83.66%); recommendations: 96 (23.76%). Top 3 placements: 43 (10.64%); first-place placements: 20 (4.95%).

Wording about the company: 105 positive, 230 neutral, 3 negative mentions. The proportion of mentions that also included a recommendation was 28.4%. The net framing score was 0.30 (defined in Methodology).

242 mentions had no recorded recommendation. Of recorded recommendations, 44.79% were Top 3 and 20.83% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Box holds the top recommendation count, supported by the widest mention base in the tracked set. Its endorsements are frequent in absolute terms, yet most mentions are neutral and many carry no recommendation at all.

Among its recorded recommendations, a substantial portion appear in top-three positions, with a smaller group placed first. The ratio of recommendations to mentions is moderate, so reach clearly outpaces endorsement in these answers.

M-Files

Questions This Section Answers

• What do the November 2026 AI answer results show about M-Files mentions, recommendations and placement?

M-Files ranks 2 by recommendation count. Mentions: 303 (75.00%); recommendations: 94 (23.27%). Top 3 placements: 51 (12.62%); first-place placements: 16 (3.96%).

Wording about the company: 101 positive, 198 neutral, 4 negative mentions. The proportion of mentions that also included a recommendation was 31.0%. The net framing score was 0.32 (defined in Methodology).

209 mentions had no recorded recommendation. Of recorded recommendations, 54.26% were Top 3 and 17.02% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

M-Files sits just behind the leader on recommendation count while appearing in fewer answers, giving it a comparatively strong recommendation-to-mention ratio. Its placements lean toward the shortlist rather than first place.

Positive wording appears often, though neutral mentions remain the majority. The profile reads as a company frequently put forward when named, with endorsement concentrated in upper-shortlist positions rather than the top slot.

DocuWare

Questions This Section Answers

• What do the November 2026 AI answer results show about DocuWare mentions, recommendations and placement?

DocuWare ranks 3 by recommendation count. Mentions: 281 (69.55%); recommendations: 85 (21.04%). Top 3 placements: 36 (8.91%); first-place placements: 10 (2.48%).

Wording about the company: 92 positive, 185 neutral, 4 negative mentions. The proportion of mentions that also included a recommendation was 30.2%. The net framing score was 0.31 (defined in Methodology).

196 mentions had no recorded recommendation. Of recorded recommendations, 42.35% were Top 3 and 11.76% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

DocuWare records a solid recommendation count on a smaller mention base than the two leaders, and its recommendation-to-mention ratio is close to theirs. First-place placements are comparatively few relative to its shortlist appearances.

Wording is mostly neutral with a sizable positive minority and very few negative mentions. The pattern suggests steady endorsement when the company appears, weighted toward shortlist rather than leading positions.

Laserfiche

Questions This Section Answers

• What do the November 2026 AI answer results show about Laserfiche mentions, recommendations and placement?

Laserfiche ranks 4 by recommendation count. Mentions: 257 (63.61%); recommendations: 84 (20.79%). Top 3 placements: 38 (9.41%); first-place placements: 10 (2.48%).

Wording about the company: 92 positive, 161 neutral, 4 negative mentions. The proportion of mentions that also included a recommendation was 32.7%. The net framing score was 0.34 (defined in Methodology).

173 mentions had no recorded recommendation. Of recorded recommendations, 45.24% were Top 3 and 11.90% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Laserfiche shows one of the stronger recommendation-to-mention ratios among the higher-ranked companies, suggesting that when it is named it is often also endorsed. Its placements are predominantly shortlist rather than first place.

Positive wording is common and negative wording rare, with neutral mentions still the largest group. The profile combines moderate reach with relatively efficient conversion of mentions into recommendations.

Dropbox Business

Questions This Section Answers

• What do the November 2026 AI answer results show about Dropbox Business mentions, recommendations and placement?

Dropbox Business ranks 5 by recommendation count. Mentions: 195 (48.27%); recommendations: 43 (10.64%). Top 3 placements: 18 (4.46%); first-place placements: 9 (2.23%).

Wording about the company: 50 positive, 145 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 22.1%. The net framing score was 0.26 (defined in Methodology).

152 mentions had no recorded recommendation. Of recorded recommendations, 41.86% were Top 3 and 20.93% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Dropbox Business appears in roughly half of the answers but is recommended in a much smaller share, so its reach considerably exceeds its endorsement. No negative wording was recorded for it.

Among its recommendations, first-place placements form a relatively large portion compared with several higher-ranked peers, even though absolute counts are modest. The profile is one of broad visibility with selective endorsement.

OpenText

Questions This Section Answers

• What do the November 2026 AI answer results show about OpenText mentions, recommendations and placement?

OpenText ranks 6 by recommendation count. Mentions: 146 (36.14%); recommendations: 24 (5.94%). Top 3 placements: 6 (1.49%); first-place placements: 1 (0.25%).

Wording about the company: 26 positive, 120 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 16.4%. The net framing score was 0.18 (defined in Methodology).

122 mentions had no recorded recommendation. Of recorded recommendations, 25.00% were Top 3 and 4.17% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

OpenText is named in a meaningful share of answers but recommended in comparatively few, giving it a low recommendation-to-mention ratio. Its placements are sparse, with first-place appearances especially rare.

Wording is overwhelmingly neutral, with a positive minority and no negative mentions. The profile describes frequent background presence rather than active endorsement in these answers.

Revver (eFileCabinet)

Questions This Section Answers

• What do the November 2026 AI answer results show about Revver (eFileCabinet) mentions, recommendations and placement?

Revver (eFileCabinet) ranks 7 by recommendation count. Mentions: 81 (20.05%); recommendations: 23 (5.69%). Top 3 placements: 8 (1.98%); first-place placements: 1 (0.25%).

Wording about the company: 25 positive, 56 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 28.4%. The net framing score was 0.31 (defined in Methodology).

58 mentions had no recorded recommendation. Of recorded recommendations, 34.78% were Top 3 and 4.35% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Revver appears in a modest share of answers and is recommended in a smaller subset, with a recommendation-to-mention ratio comparable to the leaders despite the lower absolute counts. First-place placements are rare.

Wording is mostly neutral, with positive mentions outnumbering negative ones, of which none were recorded. The profile suggests selective but reasonably consistent endorsement when the company is named.

FileHold

Questions This Section Answers

• What do the November 2026 AI answer results show about FileHold mentions, recommendations and placement?

FileHold ranks 8 by recommendation count. Mentions: 21 (5.20%); recommendations: 8 (1.98%). Top 3 placements: 3 (0.74%); first-place placements: 0 (0.00%).

Wording about the company: 8 positive, 13 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 38.1%. The net framing score was 0.38 (defined in Methodology).

13 mentions had no recorded recommendation. Of recorded recommendations, 37.50% were Top 3 and 0.00% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

FileHold has a small mention base and few recommendations, so its recommendation-to-mention ratio rests on a sparse foundation and should be read with caution. No first-place placements were recorded.

Wording is split between positive and neutral mentions with none negative. The counts are low enough that small changes would shift the ratios noticeably, so the profile is best treated as indicative rather than stable.

Templafy

Questions This Section Answers

• What do the November 2026 AI answer results show about Templafy mentions, recommendations and placement?

Templafy ranks 9 by recommendation count. Mentions: 7 (1.73%); recommendations: 4 (0.99%). Top 3 placements: 1 (0.25%); first-place placements: 1 (0.25%).

Wording about the company: 4 positive, 3 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 57.1%. The net framing score was 0.57 (defined in Methodology).

3 mentions had no recorded recommendation. Of recorded recommendations, 25.00% were Top 3 and 25.00% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Templafy has the smallest mention base in the tracked set, and its high recommendation-to-mention ratio rests on very few observations. That ratio should be read as a sparse-base result rather than a reliable pattern.

Wording is mostly positive with the remainder neutral and none negative. With so few appearances, the profile offers limited evidence about how the company is typically treated across answers.

Microsoft Power Apps

Questions This Section Answers

• What do the November 2026 AI answer results show about Microsoft Power Apps mentions, recommendations and placement?

Microsoft Power Apps ranks 10 by recommendation count. Mentions: 368 (91.09%); recommendations: 3 (0.74%). Top 3 placements: 3 (0.74%); first-place placements: 3 (0.74%).

Wording about the company: 3 positive, 365 neutral, 0 negative mentions. The proportion of mentions that also included a recommendation was 0.8%. The net framing score was 0.01 (defined in Methodology).

365 mentions had no recorded recommendation. Of recorded recommendations, 100.00% were Top 3 and 100.00% were first-place.

There are insufficient usable monthly observations for a prior-period comparison.

Microsoft Power Apps is named in nearly every answer yet recommended in only a handful, producing the lowest recommendation-to-mention ratio in the set. Its reach is the broadest recorded, but endorsement is almost absent.

Wording is almost entirely neutral, and the few recommendations that exist are all placed first. The profile illustrates most sharply how mention frequency and affirmative recommendation can diverge.

Earlier ranking snapshot context

Questions This Section Answers

• How do the available Document Management Software snapshots from July 2026 to November 2026 differ in recommendation coverage and measurement scope?

Only months with verified results are shown. Monthly sample coverage is listed in Methodology.

Only one reporting month carries verified results, so no prior-period comparison is available. The printed counts and rates describe that single sample of AI answers, and the absence of earlier months means no claim about rank stability can be made.

Counts and rates should be read together: a rate depends on the shared answer denominator, while counts show absolute endorsement volume. Neither establishes why a company was or was not recommended.

What the November Rankings Show

The rankings answer several distinct questions at once. Reach asks how often a company is named; recommendation asks whether an answer affirmatively endorses it; placement asks where an endorsement sits within a response; framing asks how the surrounding wording reads. These measures can move in different directions, and the profiles show companies with broad visibility but little endorsement alongside companies endorsed more consistently on smaller bases.

Because placements are nested within recommendations and framing is independent of both, no single figure captures a company's standing. The results describe the recorded AI answers only, not verified product facts, customer sentiment or commercial outcomes.

Methodology

Questions This Section Answers

• How were the November 2026 Document Management Software AI visibility measures counted, and what do they not establish?

This benchmark has partial coverage: 3 of 3 planned question categories contributed usable observations; 0 contributed none. This describes question-category coverage, not demonstrated platform outages. Findings apply to the available answer set.

The month in the title is the reporting period. The exact dates when the original AI answers were collected have not been verified.

Each company is counted at most once in each answer that meets the benchmark rules. A recommendation requires both an affirmative endorsement and positive wording. Mention, recommendation, Top 3 and first-place rates use the full benchmark answer total. Top 3 and first-place results are included within recommendations, not added to them.

The recommendation-to-mention ratio divides recommendations by mentions. It describes AI answer wording, not customer conversion. Net framing is positive minus negative mentions, divided by all mentions, on a scale from -1 to +1. It does not measure customer satisfaction or company quality.

Market: US; 10 tracked companies. AI services represented: ChatGPT, Copilot, Gemini, Google AI Mode, Google AI Overviews, Perplexity.

Research screening totals (answer observations can include repeated questions):

The source does not provide a reader-facing definition of “reserved”; that screening label is reported without inferring a reason for exclusion. Only the included benchmark answers form the rate denominator.

One answer can mention or recommend several companies. Adding company totals would therefore count some answers more than once. The results describe the AI answers reviewed, not independently verified facts about the companies or their products.

Monthly sample coverage:

July 2026 measured a different set of companies, so it is excluded from this comparison. August 2026 measured a different set of companies, so it is excluded from this comparison. September 2026 measured a different set of companies, so it is excluded from this comparison. October 2026 measured a different set of companies, so it is excluded from this comparison.

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

Coverage is partial: not every planned question category contributed usable observations, and findings apply only to the included answer set. The reporting month labels the period, but exact collection dates were not verified.

Each company counts at most once per answer, and a recommendation requires both affirmative endorsement and positive wording. Top-three and first-place results sit inside recommendations rather than alongside them. The recommendation-to-mention ratio describes answer wording, not customer conversion, and net framing is not a measure of satisfaction or quality. One answer can name several companies, so company totals overlap and should not be summed.