I am a solo founder building RightNow AI https://www.rightnowai.co/ , a tool that profiles, detects bottlenecks, and optimizes CUDA kernels using AI.
The idea started from my own frustration with CUDA development. Profiling and optimizing kernels was slow, manual, and often required deep GPU expertise. I kept thinking there had to be a better way.
I built RightNow AI alone. No co-founder. No early team. Every decision from the architecture to the pricing fell on me. When you are solo, there is no one to ask about the roadmap or the product. You just build, ship, and hope it works.
Technically, it has been challenging. Building models that can generate or optimize CUDA code better than manual implementations took months. Setting up serverless GPU profiling so users could test without local hardware was another major hurdle. Supporting NVIDIA's architectures like Ampere, Hopper, Ada Lovelace, and Blackwell added even more complexity.
At the same time, I had to figure out the business side. Pricing, onboarding, user feedback, scaling. Everything moves slower on the business side. There is no immediate feedback like you get when shipping code.
Today RightNow AI is live. Teams at Nvidia, Adobe, Runway, and Samsung are already using it to speed up their GPU workloads by up to 20x.
Being a solo founder is hard, but building something real that people use makes it all worth it.
If you work in CUDA, AI infra, or HPC, would love your feedback or thoughts:D
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[ 4.1 ms ] story [ 14.8 ms ] threadI am a solo founder building RightNow AI https://www.rightnowai.co/ , a tool that profiles, detects bottlenecks, and optimizes CUDA kernels using AI.
The idea started from my own frustration with CUDA development. Profiling and optimizing kernels was slow, manual, and often required deep GPU expertise. I kept thinking there had to be a better way.
I built RightNow AI alone. No co-founder. No early team. Every decision from the architecture to the pricing fell on me. When you are solo, there is no one to ask about the roadmap or the product. You just build, ship, and hope it works.
Technically, it has been challenging. Building models that can generate or optimize CUDA code better than manual implementations took months. Setting up serverless GPU profiling so users could test without local hardware was another major hurdle. Supporting NVIDIA's architectures like Ampere, Hopper, Ada Lovelace, and Blackwell added even more complexity.
At the same time, I had to figure out the business side. Pricing, onboarding, user feedback, scaling. Everything moves slower on the business side. There is no immediate feedback like you get when shipping code.
Today RightNow AI is live. Teams at Nvidia, Adobe, Runway, and Samsung are already using it to speed up their GPU workloads by up to 20x.
Being a solo founder is hard, but building something real that people use makes it all worth it.
If you work in CUDA, AI infra, or HPC, would love your feedback or thoughts:D