Atlas is the single platform for every enterprise building apps and agents. It scans and maps every AI workflow you run — so you see spend by team, project, model and use case — then optimises the workloads that don't need a premium model or a real-time SLA by running them as Deadline jobs on the cheapest provider of the model you need.
Atlas ingests your telemetry and classifies AI spend across team, project, model, use case and Capex/Opex — no production code changes.
For workloads without a real-time SLA, Atlas runs each as a Deadline job — max time, max price, a model or use case — on the cheapest provider that fits.
Durable execution with automatic retries, batched where it helps, delivered within your bounds — often at a fraction of the premium-model price.
Atlas maps your AI estate first. It ingests multi-source telemetry — via API credentials, OpenTelemetry and the Keld SDKs — and classifies spend so you can see exactly where it goes and which workloads are over-served by a premium model.
Once Atlas has mapped your workflows, it changes the unit of work. Instead of firing a prompt at one fixed model, you submit a job with the most you'll pay and the time you can wait. Atlas finds the cheapest provider of the model you need and runs it within your bounds, batching where it helps.
A job, a timeline and a ceiling price — not a prompt. Atlas runs it as a durable function with automatic retries and model selection, delivering results on completion with no polling required.
job = keld.submit(
input = transcript,
keld_use_case = "summarise", # model OR use case
keld_model = "llama-3.1-70b",
keld_deadline = "30m", # max time you can wait
keld_ceiling = "$0.60/1M", # max price you'll pay
)
result = job.await() # durable · auto-retries · no pollingSet a model or use case, a deadline and a ceiling. Atlas finds the cheapest provider of that model and runs the job within your bounds — batching where it helps.
Fully managed by Keld. Multi-AZ redundancy, 99.99% SLA, auto-scaling and managed upgrades.
Host your own Atlas in your own environment for data integrity. Air-gapped option, full ZDR support.
Switch the provider behind any model with a single config change. Run several simultaneously.
Start by mapping your AI workflows; turn on Deadline jobs when you're ready to optimise. See the bigger picture on the For Enterprises overview or talk to us about an enterprise rollout.