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SuperX.so
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Researched profile.
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What Tools SuperX.so Uses
AI-driven growth tool for creators on X.
Tools
16 tools · grouped by what SuperX.so uses
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Stripe
· 2 mentions · 2 sourcesPayments“And so I had to migrate everything over to Stripe, which is a nightmare because Stripe can automatically copy all the customers over from LemonSqueezy to Stripe because LemonSqueezy in the background uses Stripe. So they can copy the customers over.”
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“And Stripe for payments, which of course is free, well, excluding fees.”
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Tailwind
· 1 mentionOther“My essential stack is for development, I use Next.js, Node.js, and Tailwind.”
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Node.js
· 1 mentionStack“My essential stack is for development, I use Next.js, Node.js, and Tailwind.”
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Posthog
· 1 mentionAnalytics“and PostHog for analytics, which I think is free.”
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OpenAI
· 1 mentionPlatform“We use OpenAI and Anthropx Cloud Sonar API, which costs about $1,000 a month.”
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Framer
· 1 mention“Then Framer for the landing page, which costs about $10 a month.”
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Next JS
· 1 mention“My essential stack is for development, I use Next.js, Node.js, and Tailwind.”
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Screen Studio
· 1 mention“I use Screen Studio for those head-banging demos that go viral, that costs about $10 a month.”
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AWS
· 1 mention“We use AWS for our servers, which is about $200 a month.”
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SQLite
· 1 mention“For databases, I use Sqlite.”
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Cloud Code
· 1 mention“For my personal AI-assisted coding, I use Cloud Code that costs about $200 a month.”
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X API
· 1 mention“We use the X API, of course, which costs about $2,000 to $3,000 a month.”
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Anthropx Cloud Sonar API
· 1 mention“We use OpenAI and Anthropx Cloud Sonar API, which costs about $1,000 a month.”
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Zilliz Cloud
· 1 mention“Zillow's Cloud for vectorized embeddings. This lets us do semantic similarity search on tweets that costs about $200 a month as well.”
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Zillow's Cloud
· 1 mention“Zillow's Cloud for vectorized embeddings. This lets us do semantic similarity search on tweets that costs about $200 a month as well.”
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Milvus
· 1 mention“Yeah, we were using Milvus. As we were scaling, getting more users, all of a sudden now a Docker container that we were running the vectorized database embeddings on was not working. It was not able to keep up with the load, so I had to migrate that to the cloud.”
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