I'm curious about the practical applications of large language models (LLMs) that are actually generating revenue. If you've successfully monetized an LLM-based product or service:
What does your product/service do?
How did you develop and launch it?
Which LLM(s) are you using (e.g. GPT-4, Claude, open source models)?
What's your revenue model?
How much are you making (if you want to share, ballpark figures are fine)?
What challenges have you faced?
Any advice for others looking to enter this space?
I'm particularly interested in hearing about niche or unexpected applications, not just the obvious chatbots and writing assistants. Also curious about solo founders or small teams, not just well-funded startups.
Thanks for sharing your experiences!
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How did you develop and launch it?
New features for an existing product. Most of them were switched on globally when we launched them.
Which LLM(s) are you using (e.g. GPT-4, Claude, open source models)?
We started using language models before ChatGPT and friends came out. We built our models from scratch, and still use and update them.
What's your revenue model?
Saas
How much are you making (if you want to share, ballpark figures are fine)?
We don't charge extra for features that use ML, it's an implementation detail that our users don't care about. So, I am not sure what % of the whole they contribute to. Its not the majority.
What challenges have you faced?
"mlops" was a real challenge in the early days, and we built so many bespoke distributed systems to figure it out. Eventually we did, but finding the right balance between building a performant system and a system that doesn't explode in cost was tough. There is off the shelf things that do this these days, but they can be expensive.
Any advice for others looking to enter this space?
Solve problems customers are willing to pay for. Some of the features we have dreamed up have been total flops. Many of the features we have developed (ml or otherwise), while the add value for the customer and add to the moat, they aren't valuable enough that our users are willing to pay extra for it as a standalone product.