All use cases

Run AI applications & services

Build with AI. Run the services behind it.

Deploy AI applications, private model gateways and supporting services on the infrastructure your team chooses.

Start with AnkraRead the guide

For teams building ai products and internal ai services

The work to take off your team

An AI application still needs deployment, credentials, data services and operations.

Use Ankra to deploy the application and its supporting stack, including gateways such as LiteLLM or vLLM where your infrastructure supports them. Keep endpoints and credentials managed alongside the environment.

With Ankra

AI workloads connected to an operational platform.

Prepare the applicationChoose the infrastructureConnect the dependenciesOperate the service

A practical path

How this works with Ankra.

  1. 01

    Prepare the application

    Register the repository or compose a service from its Helm chart and manifests.

  2. 02

    Choose the infrastructure

    Select a cluster with the capacity, hardware and location the workload needs.

  3. 03

    Connect the dependencies

    Reuse gateway credentials, database endpoints and storage access through scoped secrets.

  4. 04

    Operate the service

    Follow deployments, logs, resource use and security findings with your team and its agents.

Follow the product guide

The platform behind the workflow

The pieces, already connected.

Applications

Turn a Git repository into a deployable application. Ankra reads your code and opens the setup for review.

Databases & platform services

Deploy open source PostgreSQL, caches, monitoring, storage and private AI gateways, with agents helping investigate and operate the stack.

Metrics, logs & health

Understand the application and the cluster underneath it, with resource views, metrics and logging integrations.

What comes next?

Keep building from here.

Build & ship

Applications and their services

Run PostgreSQL, caches, monitoring and other platform services alongside the applications that use them.

Grow & move

Multi-cloud & private infrastructure

Use one operational platform across public clouds, managed Kubernetes and private servers.

Operate & protect

An AI platform engineer

Put live infrastructure context, permissions and execution tools behind your AI workflows.

Your next chapter

You built it.
Let’s get it live.

Give your application a path to production.
Give your team a simpler way to run it.

Get your app live Try a playground

First 30 vCPU of platform usage included.
No credit card required.

From something you built
to something people use.

  • Deploy from your repository
  • Run on infrastructure you choose
  • Operate with your team and agents