FriendliAI enables organizations to realize the full potential of generative AI models with unprecedented ease, speed, and cost-effectiveness. Driven by its vision of a world where any business can harness the power of generative AI without the typical technical hurdles, FriendliAI makes it easier for organizations to deploy and scale generative AI solutions. The organization eliminates the infrastructure complexity that typically hinders the adoption of AI, allowing organizations to concentrate on innovation rather than infrastructure.

The foundation of the FriendliAI solution is a high-performance inference engine optimized for speed, scalability, and robustness. The engine integrates sophisticated model-level optimizations such as custom GPU kernels, caching, continuous batching, speculative decoding, and parallel inference with infrastructure-level optimizations such as multi-cloud scaling and resource management. This comprehensive solution provides ultra-low latency, high throughput, and cost-effective AI serving that is ideal for production use cases.

FriendliAI is designed to address the needs of enterprises and provides a guarantee of 99.99% uptime through a geo-distributed infrastructure that ensures seamless execution of workloads across geographies. With features such as built-in monitoring, compliance-friendly architecture, and flexible GPU scaling, the solution provides secure, reliable, and high-performance AI execution for critical business applications across the globe.

Solutions Offered by FriendliAI

Dedicated Endpoints

FriendliAI provides a full-featured inference solution for organizations that want to easily deploy and scale generative AI models quickly and efficiently. Using Dedicated Endpoints, organizations can deploy and run models instantly, providing consistent production-level performance even under varying workload conditions. FriendliAI’s optimized inference engine uses custom GPU kernels, caching, quantization, speculative decoding, and parallel routing to provide sub-millisecond latency and high throughput, providing a distinct advantage to businesses.

The infrastructure is designed for 99.99% availability and comes with a geo-distributed, multi-cloud architecture with automated failover and recovery. Dynamic autoscaling enables workloads to scale instantly to meet changing demand, and enterprises get access to tools for real-time performance monitoring, logging, and live model updates without downtime.

FriendliAI provides several deployment choices: Serverless for instant access without setup, On-Demand GPU instances for guaranteed performance, and Enterprise Reserved instances with discounts and special features. With SOC 2-compliant security, dedicated support, and flexible pricing, FriendliAI offers a complete solution for inference, combining blazing-fast performance, effortless scaling, and enterprise-class reliability for efficient execution of AI workloads at any scale.

Serverless Endpoints

FriendliAI Model APIs allow businesses to deploy frontier open-source model inference at scale in production with a single API call—without worrying about infrastructure. Built for speed and scalability, the service enables teams to deploy in minutes, serve billions of requests, and easily scale to dedicated resources as needed. With production-grade settings, pre-optimized models provide low latency and reliable performance from day one.

Flexible and adaptable, the APIs provide seamless OpenAI integration, enabling developers to change base URLs without modifying code. Businesses can begin with Serverless deployment and easily scale to Dedicated Endpoints for predictable throughput and workload isolation. The multi-cloud, multi-region design provides always-on reliability with automated failover and fast recovery.

Supporting multiple AI modalities, such as text and vision, the service enables advanced agentic workflows through a unified API interface. Advanced generation capabilities such as JSON mode, function calls, and schema-guided output ensure accurate and structured responses. By harnessing the power of pre-optimized open-source models, businesses can lower inference costs by 5-10x without sacrificing performance, making FriendliAI a cost-effective solution for scalable AI deployment.

Container

FriendliAI’s self-hosted inference solution allows organizations to perform high-performance AI inference on their own infrastructure, whether on-premises or within a private cloud. Using Friendli Container, this hosting solution gives organizations complete control over infrastructure, data, security, and performance, all while maintaining production-level speed and scalability.

This high-performance inference engine is optimized for demanding workloads, ensuring maximum throughput and minimum latency to achieve the necessary efficiency for large-scale AI deployment. By utilizing existing infrastructure, companies can cut GPU costs dramatically while maintaining consistent performance, resulting in tangible cost savings without sacrificing reliability.

The solution features a secure and private deployment method, ensuring that all sensitive data and models are contained entirely within the company’s internal systems, even in air-gapped settings. This solution is designed with compliance and isolation in mind, catering to companies with rigorous security needs.

FriendliAI also offers robust model tooling capabilities for real-time monitoring, logging, and workload management, providing organizations with complete visibility and control. With optimized performance, secure and private deployment, and scalable infrastructure management, FriendliAI’s self-hosted inference solution offers enterprise-class AI capabilities while maintaining autonomy and cost-effectiveness.

Byung-Gon Chun - Founder & CEO

“FriendliAI delivers 99.99% uptime SLAs through geo-distributed infrastructure and enterprise-grade fault tolerance, ensuring AI systems remain responsive during traffic spikes and scale reliably across global regions with extensive GPU support.”