IOTA is your disaggregated training infrastructure, turning scattered and underused compute into unified capacity you can train on.
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.
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.
Application / training economics
Training on compute you do not own or reserve brings the cost of a run down. That changes what is worth doing: more models become affordable to build, and you get more iterations for the same spend, so the work you had ruled out on price is back on the table.
Application / training capacity
IOTA uses compute conventional training cannot touch, so more usable capacity comes within reach. You start the work you were waiting on now, instead of holding out for a cluster to free up or paying premium rates for the little you can book.
Application / platform economics
Putting scattered, variable capacity to work keeps more of a fleet productive. Utilisation rises without buying more hardware, and workloads you could not serve profitably before become ones you can take on.
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 →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.
Outcome / training capacity
You reach capacity you could not get to before, in the shape your workload needs rather than the shape a cluster forces on it.
Outcome / infrastructure
You train and run at scale without owning, reserving, or locking into a fixed cluster you have to keep paying for.
Outcome / support
You take the managed path when you want the outcome handled, or the self-directed one when you would rather run it yourself, and the training holds together either way.
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.
Get Started →Train with IOTA
The managed route. Bring a defined workload, and we take it from qualification through to a result you can act on.
Talk to our Founding Team →