"Phase 1 is access. Phase 2 is infrastructure. We're moving from managed inference to serverless edge compute you can call your own."
Infe is built to be the invisible engine behind the world's fastest AI applications. Today, we provide the API, the routing, and the speed. But as the demand for sovereign, high-performance compute grows, we are evolving. Welcome to the era of Infe-Compute: Serverless edge inference clusters on demand.
Managed APIs are perfect for rapid prototyping, but as applications scale, the need for dedicated, predictable, and high-performance compute becomes paramount. Infe-Compute will allow you to spin up serverless inference capacity at the edge, giving you the performance of dedicated infrastructure without the overhead of managing it yourself.
Low-latency access to optimized models via our network.
On-demand inference capacity with guaranteed performance.
Dynamic capacity expansion based on real-time workload demand.
You shouldn't have to think about infrastructure. You should think about your product. Infe-Compute abstracts away the complexity of GPUs, clusters, and scaling—you just call an endpoint and get fast inference.
Consider enterprise deployment scenarios: a legal AI analyzing contracts in real-time, a medical assistant processing patient data, a financial model executing decisions. These applications demand not just speed, but guaranteed speed. Variability is not acceptable.
Unlike traditional cloud compute that lives in a handful of regions, Infe-Compute is designed edge-first. Your inference runs close to your users, eliminating the round-trip latency that kills real-time applications.
Serverless edge inference with sub-100ms guarantees. Spin up capacity on demand, pay only for what you use, and never think about infrastructure again.
Infe-Compute isn't just about raw power. It's about enabling applications that were previously impossible:
The road to Infe-Compute is about empowering builders with the infrastructure they need to push the boundaries of what AI can do. Stay tuned.