Intertakt VS SerpApi

Intertakt's answer

Most timers act like they're the main character of your workout. Intertakt acts like equipment: set it once, press start, forget it exists until it speaks. No ads interrupting your rounds. No subscription — you buy it once, the way humans buy kettles. Your playlist keeps playing. And when a call comes in, the round waits for you, not the other way around.

SerpApi's answer:

We provide more search engines under one subscription.

Intertakt's answer

People who train without an audience: home HIIT at 6 am, gym rounds, kettlebell circuits in the garage, a 4-minute Tabata between meetings. If your phone is face-down and your hands are busy — congratulations, you're the target user.

SerpApi's answer:

Developers/Companies who need data from search engines.

Intertakt's answer

Flutter, an offline-first architecture, and an unhealthy attention to audio timing. Plans are plain JSON — your training data is never held hostage.

SerpApi's answer:

Ruby on Rails and MongoDB

Intertakt's answer

Intertakt assumes you have better things to do mid-set than stare at a timer. So it doesn't need the screen. At all. Voice and beep cues ride over your music, the session survives a phone call and resumes from the exact second — and it's fully offline. Take it to the mountains where there's no signal. It was made for exactly that. 0 ads. 0 accounts. 1 tap.

SerpApi's answer:

We're the first web scraping company that focus on scraping search engines.

Intertakt's answer

Every timer asks for your eyes at the exact moment you physically can't give them. That's it. That's the whole bug report. Intertakt is what happens when you fix it properly: offline-first, cues over your music, a session that survives reality. Built by Vlad Kovnerov.

SerpApi's answer:

Back in 2017, Julien Khaleghy, the founder of SerpApi, built an iOS app that can analyze data from a picture. iOS didn't have a proper machine learning framework back then. It was challenging: iPhones' RAM were limited, no GPU or no dedicated chip acceleration were available, using only CPU was painfully slow, and compiling/porting C code from machine learning framework like Tensorflow or Caffe to iOS wasn't straightforward. Oddly, all of this wasn't the most difficult part of this project. Collecting images from Google Images was.

In these projects, 80% of his time ended up being spent on scraping and parsing Google Images. And maybe only 20% on actual machine learning model training, UI design of the actual apps, and iOS programming. This is how SerpApi was born.

Intertakt's answer

• Nobody yet — the Google Play release is in final approach
• Waitlist and founding price are live at intertakt.com; early birds keep them forever

SerpApi's answer:

• Airbnb
• Nvidia
• Meta
• Shopify
• Grubhub
• and more!