The private compute Grid.
Every server you own, rent, or reserve, run as one system. You draw the boundary; Kinesis places the work, routes around failures, and sources more capacity when you need it.
GPU and CPU compute · deploy in minutes
Build and run on compute the way no one else can
Kinesis runs your workload on the right GPU or CPU across a grid of vetted providers, with pricing that tracks real utilization and a developer experience that skips the VPCs, IAM trees, and glue work. Push code, get a running URL.
Start with what you have.
A GitHub repository, a Docker image, or your local files.Illustrative deployment · ComfyUI on the Kinesis grid
One container, anywhere
One portable Dockerfile runs across clouds, on-prem, and partner datacenters — the same artifact everywhere, with no rewrite and no lock-in.
Production-ready by default
Built-in logs, autoscaling, failover, SSL, and secrets ship with every deployment — production operations running from day one with no DevOps to wire up.
Usage-based, with a cap
On Serverless, you pay for the compute you actually use, capped at the equivalent dedicated rate. Bursty workloads pay less; steady ones never pay more.
Getting applications on the grid
Five ways onto the Grid. One system underneath.
Teams arrive from different places. The first conversation should not be about adopting our way of working. Pick an entrance. Same runtime, same placement, same operations, same bill.
GitHub repository
Connect the repo. Every push builds, deploys, and rolls forward.
Your own registry
Point us at an image if you already like your build pipeline.
Dockerfile
Hand us the build. We produce the image.
Local image
Push an image you built on your machine.
Template
Start from models, vector databases, web frameworks, or batch runners and configure from there.
We did not build five products. We built one product with five entrances.
Try it on a real app
$100 in free credit. No credit card required. Deploy your first container in under five minutes. Bring a GitHub repo, a Dockerfile, or select an template.
Yours and ours
Start on yours. Start on ours. Expand either way.
Your machines and Kinesis machines live in the same Grid. Add what you bring, or what we supply, in any order. How you deploy does not change.
Yours first
Start with hardware you already have
Connect machines you own or reserve. One Grid over what is already paid for.
What goes inside a Grid → (planned)Ours first
Start with Kinesis capacity
Need to run before a purchase order clears? Our machines join the same Grid.
The compute we supply →Either way
Expand without a second platform
Bring your own later, or buy more from us later. Mix in any amount, in any order.
See grid pricing →Increase the capacity of the compute you already own
Kinesis orchestrates your workloads across on-prem, cloud, and reserved capacity, lifting utilization from idle to near-full — so the fleet you already paid for dramatically increases its productivity.
More work from the hardware you already have
Servers sit idle from caution, not lack of work. A Grid lets your administrator decide who shares what—so the same machines carry more of your organization.
Everything you've paid for. One estate.
Hyperscaler reservations, colo cages, specialist contracts—each lives in its own world. Inside your Grid they are one estate, one interface.
When yours runs out, ours mixes in.
A deadline your fleet can't absorb. A GPU you can't get this quarter. Add Kinesis machines to the same Grid, in any amount, and bring yours back later. The mix is yours
2–10×
the value from every CPU and GPU you already own
~20%
of the open-market rental rate for the same hardware
1
fee per hardware class, not per hour of use
One system. More outcomes.
Increased capacity is just the start
The same engine that lifts your utilization spans every cloud, datacenter, and reserved contract you own — so unified cost, automatic failover, and true portability come with it, not as bolt-ons.
FinOps, automatically unified
One real-time view of cost and utilization across every cloud, datacenter, and reserved contract you pay for — including the hardware you own. The quarterly spend slide writes itself.
Operable day one
Manage workloads across every cloud, datacenter, and reserved contract from one console, with the same controls wherever they run. Your existing team operates the whole fleet, no specialized platform group required.
Configured in minutes
Connect the capacity you already have, with no proprietary configs or networking primitives to wire together. Point Kinesis at your clouds, datacenters, and reserved capacity, and the fleet is unified and orchestrating in minutes.
Case studies
Proven on real workloads
“Our partnership with Kinesis empowers us to focus on advancing generative AI in human genomics for rare diseases — while removing the infrastructure bottlenecks.”
Stanley Bishop
Head Scientist — Rare Compute
BIOTECH SIMULATION
$4.6M → $1.2M
Large-scale protein folding workloads across thousands of nodes. ~74% lower infrastructure cost through dynamic placement and utilization optimization.
AI INFERENCE PLATFORM
$120K → $45K / mo
24 production apps with highly variable demand. Lower monthly spend while improving availability and scaling responsiveness.
Questions
Questions a platform team asks first.
A private compute Grid is one control plane that covers every piece of compute an organization owns, rents, or has committed to: its own servers, colocation, cloud accounts and credits, capacity from specialist providers, and compute Kinesis supplies. Each Kinesis customer gets its own Grid. Instead of managing each pool separately, the customer submits work to the Grid, and the Grid places it on the machine that fits the rules, cost, and speed the customer set.
Request a capacity assessment.
Read-only. One number. Yours whether you buy or not. It tells you what the hardware you already have can do, and it produces the number that justifies the next step.