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Scale software delivery

for AI infrastructure

Scale software delivery

for AI infrastructure

Scale software delivery for AI infrastructure

Akuity helps teams deploy, promote, and operate AI workloads across   clusters, regions, GPU infrastructure, and customer environments —   without building and maintaining separate GitOps systems,   promotion scripts, and incident workflows.

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Problem: Where   AI delivery becomes operational work

As AI platforms scale across clusters, regions, GPU infrastructure, and customer-owned environments, delivery fragments. Platform teams have to standardize releases,   keep environments in sync, and   trace production issues back to recent changes.

One platform; to deploy, promote, and operate AI workloads

Deploy across distributed infrastructure

Run GitOps across clusters, regions, and customer environments from a managed control plane.

See application health and sync status across clusters

Connect to private environments without exposing cluster API servers

Offload control-plane upgrades, scaling, and maintenance

Promote inference
changes safely

Move images, serving config, routing rules, and infrastructure changes through controlled stages.

Require verification before changes reach production

Add approval gates for higher-risk releases

Keep a Git-native audit trail of what changed and when

Operate with delivery
context

Trace production issues back to recent deployments, promotions, and workload state.

View fleet-wide health and incident timelines

Connect alerts to recent deployments, promotions,
and cluster events

Connect alerts to recent deployments, promotions, and cluster events

Run approved troubleshooting or remediation workflows

Reference architectures

Deploy, promote, and operate AI workloads across clusters, regions, GPU infrastructure, and customer environments — without building a custom delivery platform.

GitOps for tenant-isolated environments

Manage private, tenant, or customer-owned clusters from one control plane without exposing cluster API servers.

View agent architecture docs

Tenant isolation

Outbound agent

Customer environments

Inference promotion pipeline

Move AI service changes through eval, staging, and production with checks and approvals.

Explore Kargo docs

Change sets

Approvals

Verification

Delivery-aware incident response

Manage private, tenant, or customer-owned clusters from one control plane without exposing cluster API servers.

See Intelligence docs

Recent changes

Runbooks

Runtime state

Akuity Use Cases in AI

Built for platform teams managing AI delivery at scale

Standardize delivery across clusters, regions, and tenant environments

Give platform teams one managed operating model for delivery across distributed AI infrastructure, instead of maintaining separate GitOps systems and scripts for every environment.

Control how inference changes reach production

Move images, serving config, routing rules, and infrastructure changes through repeatable stages with verification, approvals, and traceability.

Give engineering teams visibility into what changed

Help platform and infrastructure teams see what changed, where it changed, and whether a deployment, promotion, sync, or cluster event affected a workload.

Reduce self-managed GitOps operations

Offload control-plane upgrades, scaling, access, reliability work, and day-to-day maintenance while keeping familiar GitOps workflows.

Trusted by teams operation at AI scale