KWatch.io VS Makerlist

KWatch.io

Monitor Keywords on Reddit, Twitter, Linkedin, Quora, Facebook, and Hacker News. Receive an instant alert when specific keywords appear on social media.

Makerlist

A curated list of the best resources for makers

Dashboard //
2024-02-06

Define keywords to track on Reddit, Twitter, Linkedin, Quora, Facebook, and Hacker News. Once a keyword is detected on a social media platform, receive a real time alert when a keyword (email or API webhook) AI automatically analyses the context around the keyword (sentiment analysis).

Landing page //
2022-01-24

KWatch.io

Website: kwatch.io
Pricing URL: Official KWatch.io Pricing
$ Details: freemium $59.0 / Monthly
Release Date: 2024 February
Categories: #Social Media Monitoring #SEO Monitoring #Keyword Research #Digital Marketing

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Makerlist

Website: makerlist.io
Pricing URL: -
$ Details: -
Release Date: -
Categories: #Software Marketplace #Productivity #Product Discovery #Design Tools

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Category Popularity

0-100% (relative to KWatch.io and Makerlist)

KWatch.io

Makerlist

Social Media Monitoring

100 100%

Social Media Monitoring

0% 0

Software Marketplace

0 0%

Software Marketplace

100% 100

Digital Marketing

100 100%

Digital Marketing

0% 0

Productivity

0 0%

Productivity

100% 100

User comments

Share your experience with using KWatch.io and Makerlist. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, KWatch.io seems to be more popular. It has been mentiond 2 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

KWatch.io mentions (2)

Show HN: Crowdlens – AI-powered social listening
How does this solution compare to platforms like https://kwatch.io or brand24 for hacker news monitoring? Does it monitor hacker news in real time? - Source: Hacker News / 2 months ago
Who uses Google TPUs for inference in production?
I agree, except about this statement: "it wouldn’t be too difficult to port most models to Jax" --> We tried such ports at https://kwatch.io (the company I work for), and it appeared to be much harder than expected (at least for us). I don't think so many people are capable of porting an LLM based on PyTorch + GPU to Jax + TPU. - Source: Hacker News / 2 months ago