After taking some time off post-Rapid, I'm excited to share what I’ve been up to since:
@datawizzai! We’ve raised a $12.5M Seed led by
@humancapital to make AI 10x cheaper, 2x more accurate and 15x faster by transitioning from LLMs to SLMs.
AI is eating the world. But unit economics are eating AI.
Looking at the fastest growing AI products, they all share two traits - growing fast, and painful inference bills. General-purpose LLMs are just too expensive to run. A big reason for that is we train LLMs to be good at everything - answer any question, be an expert on any topic. The big labs dub this "generalisation", but for real-world applications, it is unnecessary.
In reality - many AI applications need models to be experts in one thing - and do that thing extremely well. Your coding model doesn’t need to memorize ancient recipes for Garum sauce.
This is where Datawizz comes in - we sit between the AI applications and automatically create smaller (100x-1,000x) specialized models to handle specific aspects of your work. By focusing the model and combining industry-data in the distillation process - we end up with models that beat SOTA LLMs at a fraction of the cost.
We created Datawizz to make AI specialized and scalable. We’re early in the journey, but have already been able to save companies 90% on their inference bill and speed up their apps by 10x.
Excited to build better AI platforms? Join the Datawizz team (link in first comment)