VZaps

TrustMRR

VZaps is a WhatsApp API for products, systems, and businesses that need to connect their backend to WhatsApp with stability, scale, and predictability. It's an API layer. Its goal is to allow clients

VZaps is a WhatsApp API for products, systems, and businesses that need to connect their backend to WhatsApp with stability, scale, and predictability. It's an API layer. Its goal is to allow clients to connect their own software to WhatsApp using HTTP, REST, webhooks, real-time events, and isolated instances. VZaps allows you to create instances, connect to WhatsApp via QR Code, send messages, receive events, configure webhooks, operate integrations with Typebot and Chatwoot, and monitor inst

Visit product View on TrustMRRMar 30, 2026SaaS Software B2B

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Actual performance

26customers

$189MRR/mo

Did not reach leaderboard

Traction signals

MRR growth 30d+99.4%

Launch Intel predictions

Analyze your own launch →

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

70%70% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Product HuntOn track for Day 1 leaderboard · Strong signals: using, code · Missing: mac, agents, macos

58%58% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

51%51% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

21%21% predicted probability of success on AppSumo, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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