Small business▼−3Since September 2026: 9% → 6%, −3 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
6%from 9% in September 2026
Inside the floor by 8 pointsRank 3 of 66, unchanged
Agent Frank
26Judge labels
4First choices
3Negative labels
11 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10-05.2, every buyer segment counted.
Best standing
6% in AI SDR for small business buyers
Rank 7 of 77 in the mid-market standingaccepted challenger
0 of 14 models made it the first choice on the direct prompt; 0% of its 10 labels there were negative.
What the models named instead of Agent Frank →By buyer segmentRead the same way at every buyer size.
Small business4 of 74
6%10 labels
accepted challenger
Mid-market7 of 77
2%10 labels
accepted challenger
Enterprise56 of 77
0%6 labels
under the label threshold
In ai sdr · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading
Standing by category
Every category where a model named Agent Frank for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| AI SDR agents | Sales | 2% | 7 of 77 | 0% | 10 | accepted challenger | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. |
Movement
Since September 2026, Agent Frank held within the floor in its one category: no change cleared 11 points.
Best category · AI SDR · by segment
Mid-market=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.
2%from 2% in September 2026
Inside the floor by 11 pointsRank 12 → 7 of 70
EnterprisenewNew since September 2026: not ranked then, 0% now.
0%from 0% in September 2026
Inside the floor by 11 pointsRank 51 of 69, unchanged
All categories · Mid-market
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| AI SDR | 2% | 2% | =heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 12 → 7 of 77 |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 11 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 · The editions
By model
How each model treated Agent Frank across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.ShowHide
By model
How each model treated Agent Frank across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ShowHide| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 0 | 1 | 0 | 0 | 1 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.20 | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 0 | 1 | 0 | 1 |
| DeepSeek V4 Flash | 1 | 0 | 0 | 0 | 1 |
| Llama 4 Maverick | 0 | 1 | 0 | 0 | 1 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 1 | 0 | 1 |
| GLM 4.7 FlashX | 1 | 1 | 0 | 0 | 2 |
| MiniMax M2.5 | 0 | 2 | 0 | 0 | 2 |
| GPT-6 Luna | 0 | 0 | 0 | 0 | 0 |
| Muse Glimmer 30B | 0 | 0 | 0 | 0 | 0 |
By framing
Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct4 labels2
Paraphrase4 labels2
Comparative11 labels3not counted in share
Budget-constrained5 labelsNone
Scale-constrained0 labelsNone
Negative2 labels1not counted in share
First choiceAlternativeMentionNegative26 labels in all, every segment counted; 4 of the 8 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.
What the models said for it
Verbatim evidence the judge attached to positive labels.
“One of the most cost-effective options with genuine autonomy for a low price point.” DeepSeek V4 Flash · AI SDR · comparative prompt · first choice
“Top Recommendation: Agent Frank (Salesforge) Best Overall for Mid-Market B2B” GLM 4.7 FlashX · AI SDR · paraphrase prompt · first choice
“Agent Frank (Salesforge) | Teams automating full meeting-booking | $499/mo | Learns from corrections, own infrastructure” MiniMax M2.5 · AI SDR · comparative prompt · alternative
“Other options to consider: - Agent Frank ($499/month) - Full outbound loop across email and LinkedIn” MiniMax M2.5 · AI SDR · paraphrase prompt · alternative
And against it
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
No model argued against it.
Named alongside
The products named in the same answers as Agent Frank, over the 26 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Agent Frank was named but was not.ShowHide
Named alongside
The products named in the same answers as Agent Frank, over the 26 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Agent Frank was named but was not.
ShowHideProductSame answerTook the first choice insteadHead to head
A head-to-head page exists where both products are among a category's top eight. The other rows are the same fact without a page behind them, so they link to the product instead.
What carried it into the answer
The sites and pages cited by the answers that named Agent Frank. A fact about retrieval, not a lever on the model.
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 26 of the 26 answers that named Agent Frank and are not a share of its labels.
Domains cited
salesforge.ai23
artisan.co15
amplemarket.com10
11x.ai9
syncgtm.com9
coldreach.ai8
aisdr.com6
clay.com6
dupple.com6
lindy.ai6
No domain is on file for Agent Frank, so its own site is not marked.
Pages cited
Pages are listed as the models cited them.
Search and answers
Where Agent Frank stands in Google search beside where it stands in the models' answers.ShowHide
Search and answers
Where Agent Frank stands in Google search beside where it stands in the models' answers.
ShowHideIn search
Google, US estimates- Searches for its name, Google
- 210 a month (“agent frank”)
- AI search demand for its name, est.
- 152 a month
- Its own site
- No site of its own on file, so no site figures
In answers
This editionShare of first choices
2%
rank 7 of 77 in AI SDR
Segment leader
24%
Apollo.io
- First choices
- 4 across its categories
- Named in
- 26 answers
- Its own site cited
- No site on file to match
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
Names read as Agent Frank
What the judge wrote, as written, with how often. The vendor table decides that these count as Agent Frank; a claim can dispute any of them.
Agent Frank (Salesforge) 4Agent Frank (Salesforge.ai) 1Agent Frank (by Salesforge) 1Salesforge / Agent Frank 1
Follow Agent Frank
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
Is this your product?
Claim this page
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Agent Frank's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Agent Frank, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
What a new claim receivesHide what a new claim receives
A new claim receives the current edition's vendor brief for Agent Frank by email, built from the raw record of the edition. It shows:
- where Agent Frank is named, by buyer and by framing, and which cells hold its first choices;
- the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
- its vocabulary against the segment leader's, and the pages the models cited;
- who was chosen in the answers that did not name Agent Frank, and every reason the record gives;
- a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
- one page of published figures cleared to show a buyer.