About InferX

    Sub-second cold starts,
    even for 32B (64GB) models.

    01

    Who we are

    TEAM

    We're a team of engineers with deep systems and runtime backgrounds.

    Our team is primarily based in San Francisco and Seattle, with a strong focus on low-level systems, GPU infrastructure, and performance.

    Meet the leadership team
    02

    Why we built this

    FROM FIRST PRINCIPLES

    We saw the shift toward AI infrastructure early, even when models like BERT were just starting to gain traction.

    Coming from building serverless systems on CPU, we wanted to bring the same experience to GPUs. But we quickly realized that what's called "serverless" for GPUs isn't really serverless.

    You either wait minutes for a cold start, or you keep GPUs running 24/7.

    We decided to solve this properly.

    InferX has been built over years of focused engineering, starting from first principles. Not a wrapper, not a thin layer, but a full runtime designed specifically for AI inference.

    Our goal is simple: give developers and teams a way to run models efficiently without thinking about infrastructure tradeoffs.

    03

    How we're different

    SYSTEMS, NOT SERVING

    Most systems treat inference as a serving problem.
    We treat it as a system problem.

    Instead of reloading and reinitializing models on every cold start, InferX restores the initialized state directly. This removes the need to keep GPUs warm while still achieving fast startup times.

    This changes the economics and the developer experience:

    • No need to keep GPUs idle just to avoid latency
    • Models can be truly on demand
    • High GPU utilization without sacrificing responsiveness

    THE DIRECTION

    We're building what we believe is a more natural way to run AI inference at scale.

    Get early access