IOTA
IOTA is your disaggregated training infrastructure, turning scattered and underused compute into unified capacity you can train on.
The IOTA platform
The compute already exists, the hard part is getting to it, paying for it, and putting all of it to work. IOTA removes all three, so more of your compute turns into trained models.
Problem path 01
The cost of training sets the limit on everything else: the models you can afford to build, the number of times you can iterate, the scale you can reach before the budget runs out. IOTA trains on compute you do not own or reserve, so the cost comes down and the work you had ruled out on price is worth doing again.
Problem path 02
You can have the model, the data, and the people, and still be stuck waiting on compute you can use. The capacity is out there, but it is the wrong shape, in the wrong place, or already taken. IOTA reaches that capacity and turns it into training you run now, instead of a queue you join.
Problem path 03
If you run infrastructure, the pressure is to serve more workloads and lift utilisation, without buying your way there with more hardware. IOTA puts the capacity you already own to fuller use, so more of the fleet earns its keep and more workloads become ones you can take on.
How IOTA works
Everything above comes from one idea, disaggregated training. IOTA coordinates a training run across compute that is spread out, mismatched, and always changing, and holds it together as one reliable unified system.
Core mechanism / distributed training
Conventional training needs one large block of matched, reserved hardware, held without a break for the length of the run. iota removes that requirement, coordinating the work across many distributed machines, keeping the run going even as they join and leave.
Who IOTA is for
You might train models, run a platform, or push the edge of what is possible. The constraint underneath is the same, getting more out of the compute you can reach, and IOTA is built for all three.
Train the models your budget and your cluster access would otherwise rule out, and get more iterations for the same spend, so more of what you want to build is on the table.
Explore training →Turn capacity you could not use before into training you can offer, serve more workloads, and reach the customers your cost base used to price out.
Explore platform use →Run demanding, experimental training on flexible capacity, without a reserved cluster sitting between you and the work you want to do.
Learn more →What IOTA delivers
You bring the workload, IOTA handles the compute underneath it and hands back a result you can use.
Outcome / workload economics
You train, serve, or run more for the same spend, because compute that used to sit out of reach is now doing real work.
Next step
Start building yourself, or bring us the workload and we will shape it with you.
SDK
The self-directed route. Integrate IOTA and run your own workloads, with the disaggregated training handled underneath.
Train with IOTA
The managed route. Bring a defined workload, and we take it from qualification through to a result you can act on.