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afgambin merged 8 commits into from
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docs(agentic-orchestration): update get started #7649

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docs(agentic-orchestration): update get started
afgambin Jan 5, 2026
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Backport changes to 8.8
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50 changes: 38 additions & 12 deletions docs/guides/getting-started-agentic-orchestration.md
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Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ The following prerequisites are required to build your first AI agent:

| Prerequisite | Description |
| :------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Camunda 8 environment | <p>To run your agent, you must have Camunda 8 (version 8.8 or newer) running, using either:</p><p><ul><li><p> [Camunda 8 Self-Managed](/self-managed/about-self-managed.md). For example, see [Run your first local project](../getting-started-example).</p></li><li><p> [Camunda 8 SaaS](/components/saas/saas.md). For example, [sign up for a free SaaS trial account](https://accounts.cloud.camunda.io/signup).</p></li></ul></p> |
| Camunda 8 environment | <p>To run your agent, you must have Camunda 8 (version 8.8 or newer) running, using either:</p><p><ul><li><p> [Camunda 8 SaaS](/components/saas/saas.md). For example, [sign up for a free SaaS trial account](https://accounts.cloud.camunda.io/signup).</p></li><li><p> [Camunda 8 Self-Managed](/self-managed/about-self-managed.md). For example, see [Run your first local project](../getting-started-example).</p></li></ul></p> |
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@afgambin afgambin Jan 7, 2026

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@bojtospeter Based on our conversation, my understanding is that we want to:

  1. Keep AWS Bedrock as the cloud-based LLM model linked to the SaaS experience.
  2. Add content explaining how to use a local LLM model (e.g., Ollama, following the blog) for the Self-Managed experience.

That is, AWS for SaaS and Ollama for Self-Managed? Is this correct?

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@bojtospeter bojtospeter Jan 9, 2026

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@afgambin
AWS bedrock (or other cloud based LLM provider) can be used for SaaS and Self-managed as well.
local LLM can be used only for Self-managed

So self-managed users have a bit more flexibility in this sense.

| A supported LLM provider account | <p>The AI Agent connector supports multiple model providers. This guide assumes you have access to an AWS account with permissions for the [Bedrock Converse API](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html).</p> <p> You can use a different LLM provider instead, such as OpenAI or Anthropic. For more information on how to configure the connector with your preferred LLM provider, see [AI Agent connector](/components/connectors/out-of-the-box-connectors/agentic-ai-aiagent.md).</p> |

:::important
Expand All @@ -54,19 +54,26 @@ To start building your first AI agent, you can use a prebuilt Camunda blueprint
In this tutorial, you will use the [AI Agent Chat Quick Start](https://marketplace.camunda.com/en-US/apps/587865) blueprint from [Camunda marketplace](https://marketplace.camunda.com/en-US/home).
Depending on the environment you choose, follow the corresponding steps below.

### SaaS
<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

1. In the blueprint page, click **For SAAS** and select the project you want to save the blueprint in, or create a new project and save it in this.
<TabItem value="saas">
1. In the blueprint page, click **For SAAS** and select or create a project to save the blueprint.
1. The blueprint BPMN diagram opens in Web Modeler.
</TabItem>

### Self-Managed (local environment)

<TabItem value="self-managed">
1. In the blueprint page, click **For SM** and download the blueprint files from the repository.
1. Open the blueprint BPMN diagram in Desktop Modeler or in Web Modeler.
</TabItem>
</Tabs>

### About the example AI agent process

The example AI agent process is a chatbot that you (the user) can interact with via a [user task form](/components/modeler/forms/camunda-forms-reference.md).
The example AI agent process is a chatbot that you can interact with via a [user task form](/components/modeler/forms/camunda-forms-reference.md).

<img src={AiAgentExampleDiagramImg} alt="A example AI agent BPMN process diagram"/>

Expand All @@ -89,10 +96,22 @@ For authentication, it is preconfigured to use the following connector secrets:
- `AWS_BEDROCK_ACCESS_KEY`: The AWS Access Key ID for your AWS account able to call the Bedrock Converse API.
- `AWS_BEDROCK_SECRET_KEY`: The AWS Secret Access Key for your AWS account.

You will configure these secrets differently in a Camunda 8 SaaS or a Self-Managed local environment.
You will configure these secrets differently depending on your working environment.

<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

- For SaaS and Self-Managed deployments, you can configure the secrets in the [Console](../components/console/manage-clusters/manage-secrets.md).
- For Camunda 8 Run, export the secrets as environment variables before starting the distribution. If you use Camunda 8 Run with Docker, add the secrets in the `connector-secrets.txt` file.
<TabItem value="saas">
Configure the secrets using the [Console](../components/console/manage-clusters/manage-secrets.md).
</TabItem>

<TabItem value="self-managed">
Export the secrets as environment variables before starting the distribution. If you use Camunda 8 Run with Docker, add the secrets in the `connector-secrets.txt` file.
</TabItem>
</Tabs>

## Step 3: Configure the AI Agent connector (optional)

Expand Down Expand Up @@ -134,8 +153,13 @@ When you run the AI agent process:

You can observe this dynamic behavior in real-time through Operate, where you'll see which tasks were activated and in what order.

### SaaS
<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

<TabItem value="saas">
In this example, you can quickly test the AI agent using the [Play](/components/modeler/web-modeler/validation/play-your-process.md) feature.

1. Select the **Play** tab.
Expand All @@ -147,16 +171,18 @@ In this example, you can quickly test the AI agent using the [Play](/components/
:::tip
Instead of using **Play**, you can also test the process within the **Implement** tab using **Deploy & Run**, and use [Tasklist](/components/tasklist/introduction-to-tasklist.md) to complete the form.
:::
</TabItem>

### Self-Managed (local environment)

<TabItem value="self-managed">
1. Deploy the process model to your local Camunda 8 environment using [Desktop Modeler](/components/modeler/desktop-modeler/index.md).
1. Open Tasklist in your browser. For example at http://localhost:8080/tasklist, depending on your environment.
1. On the **Processes** tab, find the `AI Agent Chat With Tools` process and click **Start process**.
1. In the start form, add a [starting prompt](#example-prompts) for the AI agent. For example, enter "Tell me a joke" in the **How can I help you today?** field, and click **Start process**.
1. The AI agent analyzes your prompt, decides what tools to use, and responds with an answer.
1. Select the **Tasks** tab in Tasklist. When the AI agent finishes processing, you should see either a `User Feedback` or a `Ask human to send email` task waiting for you to complete.
1. You can follow up with more prompts to continue testing the AI agent. Select the **Are you satisfied with the result?** checkbox when you want to finish the process.
</TabItem>
</Tabs>

### Example prompts {#example-prompts}

Expand Down
50 changes: 38 additions & 12 deletions versioned_docs/version-8.8/guides/getting-started-agentic-orchestration.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -38,7 +38,7 @@ The following prerequisites are required to build your first AI agent:

| Prerequisite | Description |
| :------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
| Camunda 8 environment | <p>To run your agent, you must have Camunda 8 (version 8.8 or newer) running, using either:</p><p><ul><li><p> [Camunda 8 Self-Managed](/self-managed/about-self-managed.md). For example, see [Run your first local project](../getting-started-example).</p></li><li><p> [Camunda 8 SaaS](/components/saas/saas.md). For example, [sign up for a free SaaS trial account](https://accounts.cloud.camunda.io/signup).</p></li></ul></p> |
| Camunda 8 environment | <p>To run your agent, you must have Camunda 8 (version 8.8 or newer) running, using either:</p><p><ul><li><p> [Camunda 8 SaaS](/components/saas/saas.md). For example, [sign up for a free SaaS trial account](https://accounts.cloud.camunda.io/signup).</p></li><li><p> [Camunda 8 Self-Managed](/self-managed/about-self-managed.md). For example, see [Run your first local project](../getting-started-example).</p></li></ul></p> |
| A supported LLM provider account | <p>The AI Agent connector supports multiple model providers. This guide assumes you have access to an AWS account with permissions for the [Bedrock Converse API](https://docs.aws.amazon.com/bedrock/latest/APIReference/API_runtime_Converse.html).</p> <p> You can use a different LLM provider instead, such as OpenAI or Anthropic. For more information on how to configure the connector with your preferred LLM provider, see [AI Agent connector](/components/connectors/out-of-the-box-connectors/agentic-ai-aiagent.md).</p> |

:::important
Expand All @@ -54,19 +54,26 @@ To start building your first AI agent, you can use a prebuilt Camunda blueprint
In this tutorial, you will use the [AI Agent Chat Quick Start](https://marketplace.camunda.com/en-US/apps/587865) blueprint from [Camunda marketplace](https://marketplace.camunda.com/en-US/home).
Depending on the environment you choose, follow the corresponding steps below.

### SaaS
<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

1. In the blueprint page, click **For SAAS** and select the project you want to save the blueprint in, or create a new project and save it in this.
<TabItem value="saas">
1. In the blueprint page, click **For SAAS** and select or create a project to save the blueprint.
1. The blueprint BPMN diagram opens in Web Modeler.
</TabItem>

### Self-Managed (local environment)

<TabItem value="self-managed">
1. In the blueprint page, click **For SM** and download the blueprint files from the repository.
1. Open the blueprint BPMN diagram in Desktop Modeler or in Web Modeler.
</TabItem>
</Tabs>

### About the example AI agent process

The example AI agent process is a chatbot that you (the user) can interact with via a [user task form](/components/modeler/forms/camunda-forms-reference.md).
The example AI agent process is a chatbot that you can interact with via a [user task form](/components/modeler/forms/camunda-forms-reference.md).

<img src={AiAgentExampleDiagramImg} alt="A example AI agent BPMN process diagram"/>

Expand All @@ -89,10 +96,22 @@ For authentication, it is preconfigured to use the following connector secrets:
- `AWS_BEDROCK_ACCESS_KEY`: The AWS Access Key ID for your AWS account able to call the Bedrock Converse API.
- `AWS_BEDROCK_SECRET_KEY`: The AWS Secret Access Key for your AWS account.

You will configure these secrets differently in a Camunda 8 SaaS or a Self-Managed local environment.
You will configure these secrets differently depending on your working environment.

<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

- For SaaS and Self-Managed deployments, you can configure the secrets in the [Console](../components/console/manage-clusters/manage-secrets.md).
- For Camunda 8 Run, export the secrets as environment variables before starting the distribution. If you use Camunda 8 Run with Docker, add the secrets in the `connector-secrets.txt` file.
<TabItem value="saas">
Configure the secrets using the [Console](../components/console/manage-clusters/manage-secrets.md).
</TabItem>

<TabItem value="self-managed">
Export the secrets as environment variables before starting the distribution. If you use Camunda 8 Run with Docker, add the secrets in the `connector-secrets.txt` file.
</TabItem>
</Tabs>

## Step 3: Configure the AI Agent connector (optional)

Expand Down Expand Up @@ -134,8 +153,13 @@ When you run the AI agent process:

You can observe this dynamic behavior in real-time through Operate, where you'll see which tasks were activated and in what order.

### SaaS
<Tabs groupId="environment" defaultValue="saas" values={
[
{ label: 'SaaS', value: 'saas', },
{ label: 'Self-Managed', value: 'self-managed', },
]}>

<TabItem value="saas">
In this example, you can quickly test the AI agent using the [Play](/components/modeler/web-modeler/collaboration/play-your-process.md) feature.

1. Select the **Play** tab.
Expand All @@ -147,16 +171,18 @@ In this example, you can quickly test the AI agent using the [Play](/components/
:::tip
Instead of using **Play**, you can also test the process within the **Implement** tab using **Deploy & Run**, and use [Tasklist](/components/tasklist/introduction-to-tasklist.md) to complete the form.
:::
</TabItem>

### Self-Managed (local environment)

<TabItem value="self-managed">
1. Deploy the process model to your local Camunda 8 environment using [Desktop Modeler](/components/modeler/desktop-modeler/index.md).
1. Open Tasklist in your browser. For example at http://localhost:8080/tasklist, depending on your environment.
1. On the **Processes** tab, find the `AI Agent Chat With Tools` process and click **Start process**.
1. In the start form, add a [starting prompt](#example-prompts) for the AI agent. For example, enter "Tell me a joke" in the **How can I help you today?** field, and click **Start process**.
1. The AI agent analyzes your prompt, decides what tools to use, and responds with an answer.
1. Select the **Tasks** tab in Tasklist. When the AI agent finishes processing, you should see either a `User Feedback` or a `Ask human to send email` task waiting for you to complete.
1. You can follow up with more prompts to continue testing the AI agent. Select the **Are you satisfied with the result?** checkbox when you want to finish the process.
</TabItem>
</Tabs>

### Example prompts {#example-prompts}

Expand Down
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