IONA

    IONA tells you what your AI infrastructure needs, before you have to find out the hard way

    It reads what's happening across your infrastructure, your models, and your pipelines, and tells you what to do next: which VM to provision, which model fits, what's breaking and why.

    IONAworking
    I need infrastructure for shelf-stock detection. Real-time, peaks at shopping hours.
    Sizing for peak: 8 vCPU, 32GB, one 8GB GPU. Want me to provision it?
    Go ahead.
    Running in ORBIT. Six resources, connections wired.
    I'll keep watching health, drift and pipelines.
    vm-gpu-01 memory is at 94% and climbing. This one needs your call.
    Type message here
    Ready
    Waiting for your request…

    How IONA Thinks for You

    Running AI in production means constant small decisions: which VM, which model, why did that pipeline just stall. IONA makes those decisions with you in real time, instead of leaving you to figure it out from scratch every time.

    1. Picks the right infrastructure and model before you build

      Recommends VM configuration and the right model for your use case, not the trendiest one.

    2. Explains production health the moment it changes

      Reads the signals across your systems and tells you what they mean.

    3. Catches model drift before your client does

      Flags when a running model's behavior starts shifting.

    4. Finds the failure point in a stalled pipeline

      No need to tear the whole thing apart to find one broken step.

    5. Guides you through recovery and closes security gaps

      Tells you what's recoverable when something breaks, and flags exposed resources like a database with a public IP before they become a breach.

    How It Works

    From use case to running infrastructure in three steps

    No guessing on VM sizing. No blind spots once it's live. IONA tells you what to run and what's happening once it does.

    IONAreading
    Your use case
    Shelf-stock detection for a supermarket chain. Real-time inference, peak load at shopping hours.
    computer visionreal-timebursty load
    Computer vision with bursty traffic. Sizing for peak, not average, so inference stays under your latency target.
    IONA recommends
    Infrastructure
    VM profileg1.gpu.8x
    Compute8 vCPU · 32GB
    GPU8GB
    Model
    SelectedQwen3.8-27B
    Whymultimodal, 262K ctx

    Built for AI-Solution Partners

    You know the use case. Let IONA handle the infrastructure decisions.

    Systems integrators and AI-solution teams use IONA to stay focused on what wins deals, not on GPU selection and VM sizing.