Installing ORCA VLMs

This article explains how to install ORCA (Optical Reasoning and Cognition Agent) VLMs and configure your instance to use them for document processing.

For information about the capabilities of ORCA VLMs, see our ORCA (Optical Reasoning and Cognition Agent) VLMs article.

Prerequisites

To successfully use ORCA VLMs:

• Your instance must support GPU-enabled application machines.

  Configure your infrastructure for ORCA VLMs

  Make sure your instance supports GPU-enabled application machines.

  • On-premise deployment: follow the instructions in the “Enabling Application Machines with GPUs” article for Docker, Podman, or Kubernetes.
  • SaaS deployment: contact your Hyperscience representative to enable GPU support in your instance.

  Learn more about Hyperscience’s GPU requirements in Infrastructure Requirements.

• Your release must contain at least one Semi-structured layout with fields.

• You need to enable the ORCA flows to start processing. Learn more in the sections below.

Installing the ORCA base model in deployments with internet access

In deployments with internet access (i.e., SaaS deployments and non-air-gapped on-premise deployments), the base model is available through a pre-configured artifact repository or Cloudsmith and can be installed directly from the platform.

Base model

A foundational model that provides core general-purpose capabilities and is not directly trained on customer-specific examples. Use-case specialization is achieved through additional training on top of the base model using customer-specific data. To learn more, see Training a Specialized Model.

Currently, Hyperscience uses the ORCA 1.0 base model.

The installation runs in the background and, once complete, enables you to use ORCA VLMs and specialize them for your use case. Follow the steps below to install the ORCA base model.

1. Go to Administration > Assets.

2. Click Install on the ORCA 1.0 card.

3. Choose how the ORCA base model should be downloaded:

• Fetch via Artifact Repository— SaaS deployments use a pre-configured repository to download the base model.
  • Fetch via Cloudsmith — On-premise deployments use a Cloudsmith key to download the base model, as your organization manages artifact access. If you don’t have the key for your account, file a ticket on our Support portal (opens in new tab).

4. Click Start.

Installing the ORCA base model in air-gapped instances

In some on-premise deployments, the instance may be air-gapped, meaning it does not have direct internet access and cannot download assets from external repositories such as Cloudsmith.

In these cases, the ORCA base model must be installed through a manual transfer process. Instead of downloading the model directly on your machine, you will:

• Download the ORCA base model assets on a machine with internet access.
• Transfer the files to your secured internal storage (e.g., S3).
• Configure an Artifacts Repository pointing to that storage.
• Install the ORCA base model from the configured repository.

Create a Semi-structured layout for ORCA VLMs

ORCA VLMs extract data only from fields defined in a Semi-structured layout. Before associating the layout with an ORCA flow, ensure it’s configured correctly.

The layout configuration affects the training payload sent to the trainer. Learn more about the trainer in our Trainer article. Proper layout configuration ensures consistent extraction behavior and reliable model performance.

Use the checklist below when creating your layout:

• Define explicit fields.
• Ensure that at least one field is defined.
• Field names reflect business meaning (e.g., “Invoice number,” “Total amount,” “Merchant name”).
• Avoid field names that don’t bring information to the model, such as “Names,” “Amount,” and “Field1.”

Configure ORCA subflows

The included flows relevant to ORCA in your instance are:

• Document Processing
• Document Processing with ORCA Subflow
• ORCA Quality Assurance Subflow.

Ensure that the ORCA base model is installed before configuring the subflow.