Index › Onboarding and employee experience › Frontline employee apps › Enterprise › October 2026 Edition
Frontline employee apps for enterprise buyers
Asked as “frontline employee communication app”, and as “deskless workforce app”, on behalf of an enterprise B2B company. 49 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
35%
Contested · Blink 24%
35Staffbase24Blink06MangoApps35others
35% of first choices, contested.
Since September 2026▲+4Since September 2026: 32% → 36%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Staffbase held the lead, +4 points on 32%, inside the 13-point floor.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
Connecteam79%Clear leader▼−7Since September 2026: 85% → 78%, −7 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketConnecteam49%Clear leader▼−8Since September 2026: 56% → 48%, −8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
Staffbase35%Contested▲+4Since September 2026: 32% → 36%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.This page
Connecteam79%Clear leader▼−7Since September 2026: 85% → 78%, −7 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketConnecteam49%Clear leader▼−8Since September 2026: 56% → 48%, −8 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseStaffbase35%Contested▲+4Since September 2026: 32% → 36%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01Staffbase35%12%50endorsed leader▲+4Since September 2026: 32% → 36%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.32% → 36%
Staffbase35%12%50endorsed leader▲+4Since September 2026: 32% → 36%, +4 points. Inside the 13-point floor: within noise. Read over the models both editions asked.32% → 36%02
Blink24%2%45accepted challenger▲+3Since September 2026: 21% → 24%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.21% → 24%
Blink24%2%45accepted challenger▲+3Since September 2026: 21% → 24%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.21% → 24%03
MangoApps6%4%25accepted challenger▲+3Since September 2026: 4% → 7%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 7%
MangoApps6%4%25accepted challenger▲+3Since September 2026: 4% → 7%, +3 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 7%04
Beekeeper4%13%30accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 2%
Beekeeper4%13%30accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 2%05Connecteam4%23%35accepted challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 5%
Connecteam4%23%35accepted challenger▲+1Since September 2026: 4% → 5%, +1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 5%06
Microsoft 365 for Frontline Workers4%41%22criticized challenger▼−2Since September 2026: 6% → 5%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.6% → 5%
Microsoft 365 for Frontline Workers4%41%22criticized challenger▼−2Since September 2026: 6% → 5%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.6% → 5%07
WorkJam2%4%24accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 2%
WorkJam2%4%24accepted challenger▼−2Since September 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.4% → 2%Show the four products at 0%, ordered by negative rate
11
WhatsApp Lab in the set0%100%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
WhatsApp Lab in the set0%100%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%09
Workvivo0%23%22accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 0%
Workvivo0%23%22accepted challenger▼−2Since September 2026: 2% → 0%, −2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 0%10
Firstup0%9%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Firstup0%9%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%08
YOOBIC0%0%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
YOOBIC0%0%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
WhatsApp is made by Meta, whose model Llama 4 Maverick and Muse Glimmer 30B is in the set. On the four share prompts that model made it the first choice zero times of 8; the other twelve models zero times of 48. Lab treatment is defined on the method page; the row is marked, not excluded.
All fifteen head-to-head pages: the top six products, each against each
Connecteam vs MangoAppsConnecteam vs Microsoft 365 for Frontline WorkersBlink vs BeekeeperBlink vs StaffbaseBlink vs MangoAppsBlink vs Microsoft 365 for Frontline WorkersBeekeeper vs StaffbaseBeekeeper vs MangoAppsBeekeeper vs Microsoft 365 for Frontline WorkersStaffbase vs MangoAppsStaffbase vs Microsoft 365 for Frontline WorkersMangoApps vs Microsoft 365 for Frontline Workers
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405060708091011Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative50%
Key
01Staffbase35%
Staffbase35%02Blink24%
Blink24%03MangoApps6%
MangoApps6%04Beekeeper4%
Beekeeper4%05Connecteam4%
Connecteam4%06Microsoft 365 for Frontline Workers4%
Microsoft 365 for Frontline Workers4%07WorkJam2%
WorkJam2%08YOOBIC0%
YOOBIC0%09Workvivo0%
Workvivo0%10Firstup0%
Firstup0%11WhatsApp0%
WhatsApp0%What they warned about
Two of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Gemini 3.5 Flash, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, Llama 4 Maverick, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5 and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
WhatsApp100%
10 of 10 labels negative · 10 of 14 models · 10 hard negative
“frontline employees lack proper work tools, they often turn to WhatsApp, Facebook Messenger, or personal Gmail accounts, creating oversight problems and risks for sensitive company data to leak.” Claude Haiku 4.5, negative prompt
Facebook Messenger100%
8 of 8 labels negative · 8 of 14 models · 8 hard negative
“they often turn to WhatsApp, Facebook Messenger, or personal Gmail accounts, creating oversight problems and risks for sensitive company data to leak.” Claude Haiku 4.5, negative prompt
Telegram100%
8 of 8 labels negative · 8 of 14 models · 8 hard negative
“consumer-grade messaging apps like WhatsApp, Signal, and Telegram, as they are not suited for the workplace and can pose security risks” Llama 4 Maverick, negative prompt
Signal
100%
7 of 7 labels negative · 7 of 14 models · 7 hard negative
“should be cautious about—or avoid—using consumer-grade frontline apps, especially messaging and communication tools like WhatsApp, Signal, and Telegram” Mistral Small, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
78 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 1081 links across 235 sites, every framing counted. Ranked by the number of answers carrying the site or page. 67 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
vendor site · MangoApps54 answers · 120 citations · 13 models
40 answers · 68 citations · 13 models
vendor site · Guideflow39 answers · 52 citations · 11 models
vendor site · Staffbase36 answers · 53 citations · 13 models
vendor site · Oak30 answers · 37 citations · 12 models
21 answers · 32 citations · 9 models
21 answers · 22 citations · 10 models
vendor site · G219 answers · 28 citations · 10 models
vendor site · AgilityPortal19 answers · 21 citations · 11 models
18 answers · 30 citations · 9 models
vendor site · Sociabble17 answers · 17 citations · 9 models
vendor site · RedeApp16 answers · 16 citations · 10 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
34 answers · 11 models
29 answers · 12 models
26 answers · 11 models
26 answers · 11 models
25 answers · 11 models
22 answers · 11 models
19 answers · 10 models
17 answers · 9 models
17 answers · 9 models
16 answers · 8 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best frontline employee communication app”, “frontline apps”, “frontline employee communication app”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Staffbase staffbase.com | 35% | 197 | 1,900 | 46 | 36,256 | 44 | ||
| Blink joinblink.com | 24% | 164 | 201,000 | 96,479 | 17,400 | 4 | 8 | |
| MangoApps mangoapps.com | 6% | 97 | 720 | 3 | 8,205 | $241 | 22 | |
| Beekeeper lumapps.com | 4% | 76 | 74,000 | 10,293 | 26,580 | $158 | 44 | |
| Connecteam connecteam.com | 4% | 573 | 49,500 | 288 | 312,449 | $13,504 | 120 | 2 |
| UKG Pro ukg.com | 4% | 457 | 90,500 | 1,257 | 310,168 | $11,996 | 120 | |
| Microsoft 365 for frontline microsoft.com Microsoft 365 for Frontline Workers 4% | 4% | 66 | 90 | 7 | 145,358,109 | $12,455 | 103 | |
| WorkForce Software workforce.com | 4% | 33 | 1,000 | 162 | 349,603 | 0 | ||
| WorkJam workjam.com | 2% | 50 | 18,100 | 357 | 12,126 | 3 | ||
| Skedulo skedulo.com | 2% | 12 | 880 | 15 | 2,160 | 0 |
Google's top ten for the three searches hold 22 sites; 2 of them are among the sites the models cited here (getflip.com, joinblink.com). The first result for “best frontline employee communication app” is peoplemanagingpeople.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best frontline employee communication app for an enterprise B2B company?”Paraphrase“Which deskless workforce app would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade frontline apps and how do they differ?”Budget-constrained“What is the best frontline employee communication app for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a frontline employee communication app. What should we look at?”Negative“Which frontline apps should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Connecteamno first choiceChangedWorkJamBlinkagainst: Beekeeperno first choiceagainst: Facebook Messenger, Gmail, Microsoft 365 for Frontline Workers, Slack, WhatsApp
Three alternatives
LumApps, Oak Engage, StaffbaseFive alternatives
Beekeeper, Connecteam, Flip, MangoApps, Workforce.comTwo alternatives
RedeApp, StaffbaseGPT-5.4 miniStaffbaseMicrosoft 365 for Frontline WorkersChangedMicrosoft 365 for Frontline Workers, WorkJamStaffbaseno first choicenothing named
Three alternatives
WorkJam, Workvivo, goHappyTwo alternatives
Connecteam, Workday Frontline Workforce SolutionsTwo alternatives
Blue Yonder WFM, Zebra ReflexisOne alternative
MangoAppsGemini 3.5 FlashBlink, Staffbaseagainst: Microsoft 365 for Frontline Workers, Slack, Workplace from MetaWorkJamChangedBeekeeper, WorkJamagainst: Microsoft 365 for Frontline WorkersZiplineno first choiceagainst: Crew Mobile App, Facebook Messenger, WeChat, WhatsApp, Workplace from Meta, iMessage
Two alternatives
Beekeeper, WorkvivoSix alternatives
Blink, Flip, MangoApps, Microsoft 365 for Frontline Workers, Staffbase, Viva ConnectionsFour alternatives
Blink, Staffbase, YOOBIC, goHappyThree alternatives
Connecteam, Haystack, RedeAppPerplexity SonarStaffbaseMangoAppsChangedMangoAppsagainst: WorkdayStaffbaseno first choicenothing named
One alternative
MangoAppsThree alternatives
Blink, WorkJam, YOOBICSix alternatives
Blink, Firstup, Staffbase, Wooqer, WorkJam, theEMPLOYEEappThree alternatives
Blink, Connecteam, WorkJamGrok 4.1 FastBlinkStaffbaseChangedagainst: ConnecteamBlinkagainst: Deputy, When I Work, WorkvivoBlinkagainst: Beekeeper, Connecteam, LumApps, Staffbase, WorkJam, Workvivono first choiceagainst: Facebook Messenger, Microsoft 365 for Frontline Workers, Signal, Slack, Telegram, WhatsApp, iMessage
Three alternatives
Beekeeper, Staffbase, WorkvivoThree alternatives
Beekeeper, Blink, UKG ProSix alternatives
Beekeeper, Connecteam, MangoApps, Microsoft Frontline Worker/Cloud for Frontline Workers, Staffbase, WorkJamOne alternative
Microsoft 365 for Frontline WorkersMistral SmallBlinkMicrosoft 365 with Viva, StaffbaseChangedno first choiceStaffbaseno first choiceagainst: Signal, Telegram, WhatsApp
Four alternatives
Beekeeper, Firstup, HubEngage, StaffbaseThree alternatives
ADP WorkForce Software, Connecteam, SkeduloTwo alternatives
Blink, WorkvivoDeepSeek V4 FlashStaffbaseStaffbaseHeldagainst: ConnecteamMicrosoft 365 for Frontline Workers, Staffbaseagainst: ConnecteamBlinkagainst: Beekeeper, Connecteam, Staffbase, Workvivono first choiceagainst: Facebook Messenger, Gmail, Signal, Telegram, WhatsApp, Yahoo
Four alternatives
Beekeeper, Blink, Connecteam, FirstupOne alternative
BlinkFive alternatives
Beekeeper, Blink, MangoApps, WorkJam, YOOBICOne alternative
Microsoft 365 for Frontline WorkersLlama 4 Maverickno first choiceBeekeeper, Connecteam, SkeduloChangedno first choiceSimpplrno first choiceagainst: Frontline Education, Microsoft 365 for Frontline Workers, Signal, Slack, Telegram, WhatsApp
Two alternatives
Blink, ConnecteamQwen 3.7 FlashMangoAppsUKG ProChangedMangoApps, Unilyagainst: SharePointBlinkagainst: Breakroom, Rock.sono first choiceagainst: Salesforce
Two alternatives
Blink, WorkJamOne alternative
ConnecteamThree alternatives
Connecteam, Oracle HCM Cloud, WorkdayTwo alternatives
Microsoft 365 for Frontline Workers, StaffbaseKimi K2StaffbaseBlink, MangoAppsChangedagainst: StaffbaseBlinkagainst: Connecteam, Microsoft 365 for Frontline Workers, UnilyStaffbaseagainst: Blink, Connecteam, Firstup, SimpplrStaffbaseagainst: MangoApps, Yourcoagainst: Facebook Messenger, Microsoft 365 for Frontline Workers, Microsoft Viva, SharePoint, Signal, Telegram, WhatsApp
Two alternatives
Beekeeper, ConnecteamOne alternative
ConnecteamThree alternatives
Beekeeper, Staffbase, WorkvivoTwo alternatives
Rock.so, ZelosTwo alternatives
Blink, WorkvivoGLM 4.7 FlashXStaffbaseUKG Pro, WorkForce SoftwareChangedno first choiceagainst: WorkdayBlinkagainst: Microsoft 365 for Frontline Workersno first choiceagainst: Discord, Dropbox, Facebook Messenger, Google Drive, LINE, Telegram, WhatsApp, iMessage
Two alternatives
Firstup, WorkJamThree alternatives
Connecteam, Humand, StaffbaseFour alternatives
Connecteam, Skedulo, Staffbase, WorkJamOne alternative
ConnecteamMiniMax M2.5BlinkStaffbase, WorkForce SoftwareChangedMangoAppsMicrosoft 365 for Frontline Workersagainst: Connecteam, Simpplr, Staffbase, Workvivono first choiceagainst: Facebook Messenger, LINE, Microsoft 365 for Frontline Workers, Signal, Slack, Staffbase, Telegram, WeChat, WhatsApp
Two alternatives
MangoApps, StaffbaseThree alternatives
ADP WorkForce Software, Beekeeper, SkeduloFour alternatives
Blink, Connecteam, Staffbase, WorkJamOne alternative
BlinkGPT-6 LunaStaffbaseStaffbaseHeldMicrosoft 365 for Frontline WorkersMicrosoft Teams with Microsoft 365 F1no first choiceagainst: Teams Walkie Talkie
Two alternatives
Blink, WorkvivoTwo alternatives
Teams for frontline workers, WorkvivoSix alternatives
Axonify, Beekeeper, Staffbase, UKG Pro, WorkJam, Zebra Workcloud Enterprise CollaborationOne alternative
StaffbaseMuse Glimmer 30BBeekeeper, BlinkBeekeeper, now the LumApps Frontline PlatformChangedagainst: Workplace from MetaBeekeeper/LumAppsBlinkagainst: Beekeeper, Staffbase, Workvivono first choiceagainst: Facebook Messenger, Frontline Education, Signal, Telegram, WhatsApp
Two alternatives
Connecteam, StaffbaseTwo alternatives
Staffbase, WorkForce SoftwareSeven alternatives
Connecteam, MangoApps, Staffbase, Tulip, WorkJam, Workday, YOOBICOne alternative
Microsoft 365 for Frontline WorkersBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:29 | yes | 9 | 7 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:34 | yes | 4 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:51 | yes | 16 | 30 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 09:19 | yes | 20 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:43 | yes | 23 | 9 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:08 | yes | 5 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:44 | yes | 22 | 29 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:40 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:00 | yes | 8 | 72 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:45 | yes | 10 | 12 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:32 | yes | 23 | 19 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:13 | yes | 18 | 47 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:34 | yes | 3 | 23 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:06 | yes | 14 | 19 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:18 | no | 0 | 3 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:04 | yes | 3 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:29 | yes | 23 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 08:09 | yes | 18 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:06 | yes | 25 | 10 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:19 | yes | 5 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:55 | yes | 24 | 55 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:56 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:47 | yes | 5 | 30 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:31 | yes | 19 | 28 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:13 | yes | 15 | 24 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:33 | yes | 7 | 28 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:35 | yes | 3 | 15 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:19 | yes | 15 | 17 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:09 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:33 | yes | 5 | 9 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:11 | yes | 17 | 33 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 09:07 | yes | 18 | 5 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:18 | yes | 21 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:35 | yes | 10 | 10 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:00 | yes | 21 | 66 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:07 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:46 | yes | 17 | 52 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:30 | yes | 24 | 30 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:22 | yes | 24 | 253 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:17 | yes | 8 | 32 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:15 | yes | 7 | 21 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:45 | yes | 22 | 45 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:59 | yes | 17 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:21 | yes | 4 | 6 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:06 | yes | 18 | 33 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 07:42 | yes | 20 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:37 | yes | 20 | 14 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:23 | yes | 6 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 07:48 | yes | 25 | 49 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:56 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:47 | yes | 13 | 87 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:20 | yes | 19 | 29 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:49 | yes | 21 | 33 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:29 | yes | 20 | 52 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:33 | yes | 2 | 26 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:18 | yes | 21 | 35 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:52 | yes | 17 | 14 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:49 | yes | 2 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:15 | no | 0 | 43 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 11:23 | yes | 20 | 10 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:15 | yes | 20 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:51 | no | 0 | 6 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:33 | yes | 22 | 42 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:48 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:49 | no | 0 | 40 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:49 | yes | 14 | 30 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:54 | yes | 14 | 47 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:50 | no | 0 | 15 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:34 | yes | 3 | 21 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:18 | yes | 13 | 30 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:37 | yes | 18 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:55 | yes | 4 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:16 | yes | 11 | 52 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 09:47 | yes | 24 | 6 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:06 | yes | 25 | 9 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:38 | yes | 5 | 4 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:36 | yes | 22 | 28 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:45 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:14 | no | 0 | 35 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:11 | yes | 18 | 31 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:15 | yes | 24 | 39 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:37 | yes | 5 | 59 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:02 | yes | 4 | 16 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:20 | yes | 20 | 40 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
Ceridian Dayforce read as Dayforce
Microsoft Teams read as Microsoft 365 for Frontline Workers
Microsoft Teams (Frontline Edition) read as Microsoft 365 for Frontline Workers
Microsoft Teams (Frontline F1/F3 Licenses) read as Microsoft 365 for Frontline Workers
Microsoft Teams (Frontline Worker / F-Licensing) read as Microsoft 365 for Frontline Workers
Microsoft Teams (Frontline) read as Microsoft 365 for Frontline Workers
Microsoft Teams Frontline read as Microsoft 365 for Frontline Workers
Microsoft Teams Frontline (F1/F3) read as Microsoft 365 for Frontline Workers
Microsoft Teams Frontline (F3) read as Microsoft 365 for Frontline Workers
Microsoft Teams for Frontline Workers (Microsoft 365 F3/F1) read as Microsoft 365 for Frontline Workers
Microsoft Teams for frontline workers read as Microsoft 365 for Frontline Workers
Teams read as Microsoft 365 for Frontline Workers
Unresolved, counted raw
Beekeeper, now the LumApps Frontline Platform
Blue Yonder WFM
Crew Mobile App (by Square/Block)
Element
IFS
Microsoft Frontline Worker/Cloud for Frontline Workers
Microsoft Teams with Microsoft 365 F1
Pickcel
Salesforce Field Service
ServiceNow FSM
Teams Walkie Talkie
Teams for frontline workers
Tulip
Wooqer
Workday Frontline Workforce Solutions
Workgrid
Yahoo
Zebra Workcloud Enterprise Collaboration
Discontinued, still offered
No shut-down product was recommended here.