Featherless.ai offers serverless AI hosting with a GPU orchestration system, simplifying the deployment and management of AI models. Their platform allows developers to run AI applications without managing underlying infrastructure, optimizing GPU utilization and reducing operational overhead.
Funding
$25M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
AVBI+5Founders
Product
Problem
Deploying and managing AI models, especially large language models (LLMs), requires significant infrastructure expertise and resources, leading to high operational overhead and costs for developers. Existing solutions often lack model variety or require users to manage complex server configurations.
Solution
Featherless.ai provides serverless hosting for LLMs, simplifying the deployment and scaling of AI applications. The platform offers access to a vast library of open-weight models from Hugging Face, eliminating the need for users to manage underlying GPU infrastructure. Featherless.ai's unique model loading and GPU orchestration capabilities ensure optimal performance and cost-efficiency. Developers can access and utilize these models via API, enabling them to focus on building AI-powered applications without the complexities of server management.
Target Audience
The primary target audience includes AI developers, researchers, and businesses seeking a simplified and cost-effective solution for deploying and scaling LLMs without managing infrastructure.
Features
- Serverless inference for a wide range of LLMs, including Llama 2 and 3, Mistral, Qwen, and DeepSeek.
- Access to over 4300+ compatible models from Hugging Face.
- GPU orchestration system optimizing model loading and utilization.
- Support for models with context lengths of 4k, 8k, or 16k tokens.
- API access for seamless integration into various applications.
- No logging of prompts or completions sent to the API.
- Support for fine-tunes of Llama 3 15B, Llama2 SOLR (11B).
- Models served at FP8 precision for optimized inference speeds.