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Recently Funded|Amount: USD 8.5M|Industry: Software Development
Mako Raises $8.5M Seed Round to Revolutionize AI-Driven GPU Optimization
Mako

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Mako is thrilled to announce that we have successfully raised $8,500,000 in our latest funding round, a significant milestone that marks a new chapter in our company’s evolution. Formerly known as A2 Labs, Mako has been at the forefront of revolutionizing GPU optimization by eliminating the need for expensive, manual tuning processes that have long been a bottleneck in high-performance computing. Our innovative suite of products is designed to empower developers and organizations by streamlining and automating tasks that traditionally required extensive expertise and resources. MakoGenerate, our AI agent, is a prime example of this vision in action—it writes and validates GPU kernels in CUDA, Triton, and more, ensuring that performance-critical code is both efficient and reliable. Meanwhile, MakoOptimize automatically tunes hyperparameters in cutting-edge frameworks like vLLM and SGlang, maximizing performance and saving precious time for teams striving to push the boundaries of AI and scientific computing. The funding will be strategically deployed to accelerate our R&D efforts, enabling us to further enhance our technology stack, expand our product offerings, and scale our operations to meet growing global demand. This capital injection not only validates our pioneering approach but also strengthens our commitment to driving innovation in the rapidly evolving GPU optimization market. With renewed momentum and a robust financial foundation, Mako is poised to continue delivering transformative solutions that lower operational costs, boost efficiency, and empower users to harness the true potential of GPU acceleration without the need for costly and time-consuming manual intervention.
Buying Signals & Intent
Our AI suggests Mako may be interested in solutions related to:
- GPU Hardware
- AI Solutions
- Cloud Deployment Services
- Performance Monitoring Tools
- Machine Learning Frameworks
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