Use IOTA
Two ways in. One platform.
However you come to IOTA, the platform underneath is the same. Pick the route that fits how you want to work, run it yourself, or hand it to us.
Choose how you use IOTA
The only real question is how much you run yourself.
Integrate IOTA and drive your own workloads, or bring us the workload and we take it from start to result. Same platform, same capability, whichever you pick.
SDK
Self-directed technical route
Integrate IOTA and run your own workloads, with direct control over how they are configured and executed.
- Who it's for
- Teams with the technical capability to run their own training, and the infrastructure people to integrate a platform directly.
- What you do
- Configure your workload, connect to IOTA, and run it. You keep control of the workload, IOTA coordinates the compute underneath it.
- What IOTA handles
- The disaggregated training underneath, from coordination and execution to monitoring, recovery, and reporting.
Train with IOTA
Managed route
Bring us a defined workload, and we take it from qualification through to a finished, reported result. The managed route suits model-training workloads and platform or fleet workloads alike.
- Who it's for
- Teams and platforms that want the outcome without running the training themselves, or that want it qualified and managed end to end.
- What you do
- Bring the workload, the objective, and what a good result looks like. We shape it with you and run it.
- What IOTA handles
- Everything from qualification and configuration through to execution, monitoring, recovery, and a result you can act on.
Which route fits your situation?
Find the one that sounds like you.
The right route usually comes down to how much you want to run yourself. Here is where each one tends to fit.
Scenario 01
Experienced ML team with a defined training workload
You have the expertise and the workload ready. Integrate directly and run it yourself.
SDK →Scenario 02
A company that wants to train its own model but lacks distributed-training expertise
You know what you want to build, but not how to run it across disaggregated compute. We take that on with you.
Talk to our Founding Team →Scenario 03
An AI platform with workloads that are hard to serve profitably
You have demand you cannot serve profitably today. We help you turn capacity you could not use before into workloads you can take on.
Talk to our Founding Team →Scenario 04
A GPU operator with an AI workload backlog or capacity sitting idle
You have the hardware and the demand, but not the layer that matches them. Integrate IOTA and put more of the fleet to work.
SDK →Scenario 05
An advanced research team with a defined workload and strong internal expertise
You have the capability and a clear objective. Run it yourself, on flexible capacity, without a reserved cluster.
SDK →Scenario 06
A commercially important workload that needs qualification and managed execution
The workload matters too much to leave to chance. We qualify it, run it, and report back on the result.
Talk to our Founding Team →Fault-tolerant training
Built to keep going when the hardware doesn't.
Disaggregated compute is never perfectly reliable. Machines slow down, drop out, and rejoin. IOTA is built so none of that stops the work, and so progress is preserved rather than lost.
Fault-tolerance concept
Failure without lost work
Work is spread so no single machine holds the only copy of a result. A large share of the machines in a stage can fail, and the combined output still comes together correctly, with over 99% of the work accounted for.
Built for real training workloads
Not a demo. A platform with a track record.
IOTA is proven on real workloads, at scale, in the open. You can see how it holds up before you commit.
Next step
Two ways in. One platform underneath.
Start building yourself, or bring us the workload and we will shape it with you.
Train with IOTA
The managed route. Bring a defined workload, and we take it from qualification through to a result you can act on.