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Omnivery Bot Detection API

Know which email opens and clicks are real humans, not bots

A huge share of email opens and clicks aren't people: security scanners (Proofpoint, Mimecast, Defender) pre-click links, Apple MPP fires phantom opens, and botnets inflate engagement. The Omnivery Bot Detection API returns a simple is_bot verdict per event, so your analytics, automation, and ad payouts run on real humans. Built on 20+ proprietary datasets over 8+ years, with batch and single-event modes and honeypot detection. Beehiiv uses it to block $2M+/month in newsletter ad fraud.

Top comment

Hi Product Hunt! I'm Jakub, founder of Omnivery.

Here's a problem almost every email team has and almost no one measures: a huge share of your "opens" and "clicks" aren't people. Security scanners (Proofpoint, Mimecast, Barracuda, Microsoft Defender) often click every link in an email before it reaches the inbox. Apple's Mail Privacy Protection fires opens for users who never looked. Botnets inflate engagement on purpose. If you trigger automation off that data - send-time optimization, re-engagement, lead scoring, ad payouts - you're reacting to machines.

We built the Omnivery Bot Detection API to fix that. Send it an email event, it returns a simple is_bot verdict. That's it.

What's behind that simple answer:

  • 20+ proprietary datasets built over 8+ years of deliverability work

  • Detection across security scanners, Apple MPP, inbox-tracking tools, and botnet click fraud

  • Batch mode (up to 500 events) or single-event; honeypot detection built in

  • Hashed identifiers, no PII sharing, EU infrastructure

The proof point we're proudest of: Beehiiv uses it to block more than $2M/month in newsletter ad fraud by filtering bot clicks out of what advertisers pay for.

It came out of running email infrastructure for 18 years (first as Mailkit) - we needed this internally, kept refining it, and realized no other transactional provider offers anything equivalent. So we opened it up as a standalone API and for white-label use by other ESPs.

I'd love your feedback - especially from anyone doing newsletter ads, engagement scoring, or send-time optimization. How are you handling bot and MPP noise in your metrics today? Ask me anything.

About Omnivery Bot Detection API on Product Hunt

Know which email opens and clicks are real humans, not bots

Omnivery Bot Detection API was submitted on Product Hunt and earned 9 upvotes and 2 comments, placing #68 on the daily leaderboard. A huge share of email opens and clicks aren't people: security scanners (Proofpoint, Mimecast, Defender) pre-click links, Apple MPP fires phantom opens, and botnets inflate engagement. The Omnivery Bot Detection API returns a simple is_bot verdict per event, so your analytics, automation, and ad payouts run on real humans. Built on 20+ proprietary datasets over 8+ years, with batch and single-event modes and honeypot detection. Beehiiv uses it to block $2M+/month in newsletter ad fraud.

On the analytics side, Omnivery Bot Detection API competes within Email, Messaging and API — topics that collectively have 187.1k followers on Product Hunt. The dashboard above tracks how Omnivery Bot Detection API performed against the three products that launched closest to it on the same day.

Who hunted Omnivery Bot Detection API?

Omnivery Bot Detection API was hunted by Jakub Olexa. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

For a complete overview of Omnivery Bot Detection API including community comment highlights and product details, visit the product overview.