Featherless.ai, a Singapore-based artificial intelligence infrastructure firm, has secured $20 million in Series A funding to expand its platform for deploying open-source AI models.
The round was co-led by AMD Ventures and Airbus Ventures, with participation from BMW i Ventures, Kickstart Ventures, Panache Ventures, and Wavemaker Ventures.
Featherless.ai said it will use the capital to scale its global infrastructure, launch a dedicated marketplace for specialised open models and deepen technical integration with multiple hardware architectures.
The company aims to reduce the cost of AI inference while offering enterprises an alternative to proprietary compute environments.
The firm currently supports more than 30,000 open models across language, vision and audio. Its platform allows developers to deploy production-grade AI models without being tied to a single cloud provider, chipmaker or closed technology stack.
“When a few dominant players control the entire stack, it stifles competition and limits what developers can imagine,” said Eugene Cheah, chief executive officer and co-founder of Featherless.ai.
Cheah said the company is building infrastructure that makes open-source AI practical and reliable at scale, allowing enterprises to build on systems they own rather than platforms they merely rent.
Featherless.ai said its infrastructure is hosted in the US and EU, with a global team across Canada, Europe, the US, Singapore and Australia.
The company said this supports demand for sovereign AI, where enterprises need greater control over jurisdiction, data privacy and model deployment.
Through a strategic collaboration with AMD, Featherless.ai ensures popular open-source models run natively on the AMD ROCm software platform.
The company said this provides a competitive and auditable alternative to proprietary hardware systems.
Sagi Paz, head of AMD Ventures, said Featherless.ai is helping expand access to open-source AI and support a more competitive ecosystem.
The company said its founding team created RWKV, an open-source architecture designed to challenge the dominance of transformer-based models.
The funding highlights continued investor appetite for AI infrastructure companies that support open, decentralised and enterprise-controlled technology stacks.
As AI adoption shifts from experimentation to production, platforms that lower inference costs and reduce reliance on closed ecosystems may become increasingly important for fintech, enterprise software and digital finance applications.