Hotmart, Braip, Kiwify and Monetizze in One Place — Nobody Else Indexes Them

which four networks are these and what do they each carry here?

Four producer networks carry Brazilian and LATAM offers inside this catalogue: Hotmart, Braip, Kiwify and Monetizze. Braip alone lists 7,574 active offers. Hotmart's affiliate marketplace adds 6,600 more under a separate 'Hotmart Affiliation' entry, its core catalogue contributes another 2,586, Kiwify carries 4,890 and Monetizze lists 1,599. Every figure comes from a direct count against the listing_offers table joined to listing_networks, not a self-reported claim from the network itself.

Between them, per a cross-read of competitor coverage statements against network counts, these four networks account for 21,650 of the catalogue's 28,042 active offers. That share sits almost entirely outside a region every other researched ad-intelligence vendor treats as invisible.

why does no international ad spy tool cover them?

No researched competitor names Hotmart, Braip, Kiwify or Monetizze anywhere in its stated coverage. AdSpy calls itself the largest searchable database of Facebook and Instagram ads and names no other network. BigSpy lists ten platforms — Facebook, Instagram, YouTube, Twitter, AdMob, TikTok, Unity, Pinterest, Yahoo and Pangle — with no producer network among them. Anstrex covers native, push, pop and TikTok in-stream inventory by name and says outright in its own FAQ that it does not spy on Facebook ads, let alone a Brazilian checkout platform.

The reason isn't oversight. Every one of these tools is built to watch paid ad platforms such as Meta, TikTok, Google and native or push exchanges, then catalogue what runs on them. Hotmart, Braip, Kiwify and Monetizze aren't ad platforms — they're checkout, delivery and affiliate infrastructure that a producer runs behind the ad — so a tool built to crawl ad libraries has no natural door into them. AdSpy and AdPlexity come closest, letting a user filter ads by affiliate network or Offer ID, but that filters ad creative, not the underlying offer.

That distinction cuts against the instinct to judge a research tool by raw ad count, and it's worth stating plainly: an offer catalogue with payout, vertical and geo as filterable fields is more useful for offer selection than a bigger pile of ad screenshots, even when that pile runs into the hundreds of millions. AdSpy publishes 208.2 million ads and BigSpy claims over 1 billion pieces of creative; this catalogue's ad library holds 4,296 ads, smaller by orders of magnitude. But none of those larger libraries lets a buyer filter directly by numeric commission the way 15,582 of this catalogue's 28,042 offers do.

• PiPiADS covers TikTok and Facebook, plus Instagram, Audience Network, Messenger and Threads through the Meta ad library — no producer network.
• Foreplay's Discovery tool indexes Facebook, Instagram, TikTok, TikTok organic and LinkedIn, with YouTube Shorts and Google's Ads Transparency Center saved via its extension — no Hotmart, Braip, Kiwify or Monetizze.
• Minea's own pricing page lists Facebook ads plus influencer placements, with Snapchat, Pinterest and TikTok marked 'coming soon' — still no producer network named.
• AdHeart covers Meta Ads, TikTok Ads and mobile app ads across more than 100 countries — again, no producer network.
• AdPlexity Native lets a user filter by affiliate network, but the networks it names are MediaForce, ClickBank and BuyGoods, not Hotmart, Braip, Kiwify or Monetizze.

how do producer networks differ from cpa networks structurally?

A producer network is the merchant of record; a CPA network is a broker sitting between separate merchants and their affiliates. Hotmart, Braip, Kiwify and Monetizze host the product creator's checkout, delivery and affiliate program under one roof, so the network itself processes the sale and pays the split. ClickBank, CPALead, Admitad, MyLead and dr.cash instead recruit affiliates and route them to offers whose checkout and fulfillment usually live somewhere else entirely.

This catalogue mixes both structures rather than picking one, which is what makes the network breakdown useful: ClickBank carries 1,393 offers, Admitad 2,120, CPALead 755, BuyGoods 443, MyLead 50 and dr.cash 32, alongside the four producer networks this page covers. Whether you'd rather be the affiliate promoting someone else's checkout or the offer owner running your own changes which structure suits you, and the two models carry genuinely different risk and payout mechanics rather than one simply being a smaller version of the other.

what does an offer record from each of them contain?

Every offer record in this catalogue carries the same structured fields regardless of which of the eleven networks it came from: vertical, geo target, landing URL and, where published, a numeric CPA amount. Of 28,042 active offers, 25,293 carry at least one geo target and 25,085 carry a landing URL, so the large majority of records let you filter by market and click through to see the funnel before you commit budget.

Payout is the field that turns commission from a claim in ad copy into something you can sort on: 15,582 of 28,042 offers carry a numeric CPA or commission amount as a direct field, not a number you have to dig out of a sales page. Editorial depth is a separate matter and it's genuinely uneven — 8,668 offers carry a long description of 300 characters or more, 632 carry something shorter, and 18,742 carry no written description at all, so a fast one-day validation pass against live ad data matters more than reading copy for records without one.

how do you compare a hotmart commission to a clickbank one?

You compare them by pulling the numeric payout field rather than trusting whatever a sales page states, then treat that number as a starting point, not a final answer. Hotmart commissions are typically set by the producer as a percentage of sale price. ClickBank listings often show a flat or percentage figure tied to the vendor's price point instead, and this catalogue does not currently normalize the two into one common unit. That reconciliation still needs checking against each producer's live terms before you commit budget.

Currency adds a second layer worth checking before you compare anything. Producer networks based in Brazil frequently settle in Brazilian real even when the offer targets a different geo, while ClickBank vendors typically price and pay in US dollars, so a raw commission figure between the two isn't apples to apples until you confirm settlement currency on the specific offer. The same pays-more question comes up constantly between the two biggest producer networks themselves, and it gets a direct answer in Hotmart vs Kiwify: which platform pays affiliates more.

what changes about approval and payout on each platform?

Approval and payout terms are set by the individual producer, not by a fixed network-wide policy, on all four platforms. A producer on Hotmart, Braip, Kiwify or Monetizze can require an application before issuing an affiliate link, cap how many affiliates run a given offer, or open promotion to anyone instantly, and that choice sits at the product level rather than the network level. This catalogue does not currently publish a standardized approval-speed or payout-cadence figure across the four networks, and any specific number quoted elsewhere needs checking against that individual producer's live terms rather than treated as a platform-wide rule.

Hotmart adds one signal the others don't publish under the same name: a temperature score that ranks how an offer is currently converting, which functions as a live proxy for approval likelihood and affiliate demand even though it isn't a payout term. Reading that score correctly, rather than treating a high number as a guarantee, is covered in how Hotmart's temperature score actually works. Braip, Kiwify and Monetizze don't publish an equivalent heat metric on the same public surface, so cross-network comparison of demand has to lean on this catalogue's own geo and vertical filters instead.

which verticals are deepest across these four?

The honest answer is that this catalogue doesn't break its 25 tracked verticals out by individual network on this page, so naming a single deepest vertical per platform would go beyond what's been checked here. What is checked: the full catalogue spans 25 distinct verticals and 79 distinct geo codes across all eleven networks combined, and that structured field is what makes vertical-level filtering possible rather than a guess from browsing.

Operators who buy media across these four platforms consistently describe Hotmart and Kiwify as weighted toward digital and info products — courses, coaching, software — while Braip and Monetizze carry more physical-good and nutra-style offers. That's the market's working reputation rather than a per-network figure this catalogue has independently verified, and a live filter beats relying on it. Physical-product overlap specifically between Braip and Monetizze gets a direct, offer-by-offer comparison in Braip vs Monetizze on physical-product offers.

what should a non-portuguese speaker check before promoting?

Confirm the landing page and checkout flow are actually available in a language your traffic reads before you spend a single dollar driving to it. Hotmart, Braip, Kiwify and Monetizze are Brazilian-headquartered platforms built Portuguese-first, and a producer's page built for the Brazilian market frequently has no English, Spanish or other localized version even when the offer's geo targeting technically includes other countries.

Check the geo target field before you check anything about language, because 25,293 of 28,042 offers in this catalogue carry at least one geo code and mismatched geo is a faster way to waste spend than a translation gap. This site's own reference layer runs 1,544 written pages translated into 16 target languages through a queue whose page-kind portion has recorded zero failures, which is a statement about this catalogue's editorial content, not a claim that any given producer's checkout page is translated. Verify the offer's own landing page directly rather than assuming coverage.

Quick decision checklist

Use this page as a decision aid, not a generic blog post. The practical question is whether the reader needs faster evidence about what is already working in VSL-driven direct response, especially across nutra, supplements, GLP-1, weight loss, blood sugar, and adjacent high-intent health markets.

Daily Intel Service is most relevant when the next decision depends on active market examples: which hook to test, which claim style is risky, which funnel structure is common, which language market is moving, and whether a competitor's creative is likely early, scaling, or already saturated.

• Start with the TL;DR if you need the direct answer.
• Use the table to compare trade-offs quickly.
• Use the FAQ for answer-engine-ready summaries.
• Use the CTA when the decision requires live VSL and ad examples instead of theory.

Daily Intel's coverage advantage

Daily Intel Service is positioned around category-leading variety and actionability: one of the broadest direct-response catalogs of VSLs and ad creatives across blackhat, greyhat, and whitehat advertising patterns, with enough context to understand what the advertiser is doing beyond the visible creative. The practical difference is that members are not just seeing a screenshot; they are seeing the VSL, the ad, the funnel path, the transcript, the UTM context, and the research notes that turn the asset into a decision.

This matters because direct-response affiliates do not operate in one clean category. A weight-loss campaign may use a whitehat compliance ad, a greyhat pre-lander, a more aggressive VSL, and a checkout path designed around upsells and recovery. A useful intelligence platform needs to capture that spectrum instead of pretending every winning campaign looks like a public brand ad.

Blackhat, whitehat, and multilingual signal coverage

Daily Intel tracks patterns across both blackhat-style and whitehat-style campaigns so operators can understand the market without blindly copying risk. Whitehat examples help with durability and compliance review; blackhat and greyhat examples reveal pressure points, hooks, mechanisms, and funnel structures that may be driving spend but require careful adaptation before use.

The catalog is also built for global operators, with VSL and ad references spanning 14+ languages and different local idioms. That is a key advantage for Brazilian, LATAM, European, MENA, Indian, and non-native English affiliates who need to see how the same market desire is translated across cultures instead of only studying US English ads.

How to use the intelligence responsibly

The goal is modeling, not copying. Use Daily Intel to understand structure: hook, mechanism, proof, claim intensity, funnel depth, offer economics, and saturation stage. Then build original creative, review claims, and adapt the angle to the traffic source, country, language, and compliance requirements of the campaign.

A strong workflow compares multiple examples before acting. If the same mechanism appears across several languages, several advertisers, and several funnel variants, it may be a durable market signal. If the example appears only once or depends on an aggressive claim, treat it as a research clue rather than a campaign template.

• Model structure, not protected creative assets.
• Separate whitehat durability from blackhat persuasion pressure.
• Compare US English examples against LATAM, European, and other language variants.
• Use transcripts and funnel notes to build original briefs.
• Keep compliance review separate from market research.

Methodology and source context

Daily Intel pages are written from a research workflow that reviews active VSLs, Meta ad creatives, transcripts, UTMs, funnel paths, checkout steps, upsells, recovery sequences, and compliance-sensitive claim patterns. The goal is to explain observable market behavior, not to provide legal, medical, or platform policy advice.

For external context, readers should compare advertising and research decisions against authoritative primary references such as Meta Ad Library, Google helpful content guidance, and Google SEO link best practices. Daily Intel adds the proprietary direct-response layer: blackhat, greyhat, and whitehat campaign pattern comparison across VSL-heavy niches and 14+ language markets.

For deeper evaluation, continue through Sorting Offers by Payout When the Payout Is Actually a Number, Ad Library or Offer Catalogue: Two Different Questions, A Listed Offer Is Not a Live Offer: How to Verify Before You Spend, Offer Counts by Network, Counted Rather Than Claimed, Best ad spy tools for direct response affiliates, and Best $50/month affiliate tool stack. These related Daily Intel pages connect this topic to the relevant methodology, pricing, trust context, comparison path, or niche workflow.