Ai Blueprints
HP AI Studio (Ai Blueprints) — secure, GPU-powered local AI development with pre-built blueprints and 1-click containers.
Last verified:
What is Ai Blueprints?
HP AI Studio (Ai Blueprints) is a centralized desktop application and cloud-native, GPU-powered development platform for data scientists and AI engineers. HP AI Studio provides a simple, safe way to create, collaborate on, and deploy on-premises AI projects: one-click containerized setups that eliminate Docker complexity, pre-built production-ready AI blueprint templates with tested architectures, GPU-optimized workspaces, portable reproducible projects with peer-to-peer syncing, automatic MLflow experiment tracking, the NVIDIA NGC catalog of pre-trained models, and the Z by HP Data Science Stack Manager. Supports hybrid compute across local, on-prem, and cloud, with secure remote access via HP Z Remote Graphics Software — for teams that need to keep data, logic, and IP private.
Ai Blueprints pricing
Pricing model: Freemium
HP AI Studio offers a Free tier and a Pro tier. Free tier (best for individual data scientists) includes: basic blueprints, pre-defined workspaces, customizable workspaces, 5 projects limit, container export, local/remote storage connection, NVIDIA NGC Catalog access, model artifacts management, local jobs, and community support. Pro tier (best for data science teams) includes all free features plus: unlimited projects, private projects, account switching, account compute, seat management, role-based access, HP Support, collaboration features, and SSO. Pro provides guaranteed access to premium GPUs like A100s and H100s, multi-GPU training, enterprise-grade security with audit logs, and full MLOps support with CI/CD pipelines.
Ai Blueprints pros
- One-click containerized environments eliminate Docker complexity
- Pre-built blueprints reduce development time significantly
- GPU-optimized workspaces ready for immediate coding
- Portable projects work across devices without manual setup
- Peer-to-peer syncing for data and project code
- Automatic experiment tracking with MLflow integration
- Access to NVIDIA NGC catalog with pre-trained GPU-optimized models
- Z by HP Data Science Stack Manager for easy tool installation
- Supports PyTorch, TensorFlow, Hugging Face, and local LLMs
- Container export allows running projects anywhere
- Keep data, logic, and IP private with local deployment
- Role-based access control for team security
- TPS 1.2+ encryption for data in transit and AES 256 for data at rest
- Free tier includes up to 5 concurrent projects
- Customizable workspaces fit any workflow needs
Ai Blueprints cons
- Free tier has no guaranteed GPU access with possible queue waits
- Free tier limited to only 5 projects maximum
- Session timeouts and memory caps on free tier restrict large jobs
- No team collaboration tools in free tier
- No CI/CD integration available in free tier
- Free tier may assign lower-tier GPUs like NVIDIA T4s
- Requires Windows 11 or Ubuntu 22.04 with specific hardware
- Needs minimum 16GB RAM and 50GB storage
- GPU compute requires NVIDIA GPU with driver 528.89 or newer
- Cloud services hosted only in US data centers with no region choice
Frequently asked questions about Ai Blueprints
What is HP AI Studio?
Z by HP AI Studio is an enterprise-grade platform designed for collaboration in local compute environments. It is a centralized desktop application specifically developed for data scientists and engineers that lets you connect to multiple data sources, create, collaborate, and deploy on-premises AI projects. Users can create an account, download and install the app on Windows or Linux, and invite collaborators to start creating AI projects locally and accelerate AI model development.
What operating systems and hardware does HP AI Studio require?
HP AI Studio requires Windows 11 or Ubuntu 22.04, Intel Core i5 12th gen or higher, AMD Ryzen 9 or higher processors, minimum 50 GB of available storage, 16GB of RAM, and Internet access. To enable GPU compute, HP AI Studio requires any NVIDIA GPU compatible with driver version 528.89 or newer.
What are blueprints in HP AI Studio?
Blueprints are production-ready templates that provide tested architectures and workflows to help you build sophisticated AI applications in a fraction of the time. Instead of starting from blank files, you build from blueprints that you can customize to fit your workflow. They reduce development time and effort by providing ready-to-edit examples for custom AI use cases with modular building blocks.
How does data security work in HP AI Studio?
AI Studio uses multiple security technologies: data in transit is protected using TLS 1.2 or better, data at rest is protected using AES 256 encryption, RBAC controls access to data, only users with business need get access to customer data, periodic RBAC access reviews are performed, JWT tokens are used for authorization to cloud services, and sensitive data is anonymized using SHA256 or one-way hash before storage. The platform undergoes penetration testing, static code analysis, and container scanning.
What cloud technology does AI Studio use?
AI Studio services are hosted on Amazon Web Services (AWS). All data associated with a given account is hosted in a single data center. AI Studio persists product and usage data in MongoDB and uses HP-ID as an Identity Provider for user authentication. AWS data centers are Tier 3+ and AWS handles physical and environmental security including protection against fire, flood, and earthquakes.
How does project reproducibility work in AI Studio?
Project reproducibility is achieved through containerized workflows that make it easy to share and use projects across devices without manual setup. When you connect collaborators, they can reproduce exact environments, reducing manual setup and package conflicts across devices. Peer-to-peer syncing handles data, experimentation tracking, and project code across users and devices. If peer-to-peer connection isn't possible due to network restrictions, a cloud relay facilitates transfer while maintaining end-to-end encryption.
What is the difference between Free and Pro tiers?
The Free tier includes up to 5 concurrent projects, prebuilt AI environments, automatic experiment tracking, exportable Docker containers, NVIDIA NGC model access, and community support. The Pro tier adds unlimited projects, private projects, account switching, account compute, seat management, role-based access, HP Support, collaboration features, and SSO. Pro also provides guaranteed access to premium GPUs like A100s and H100s, multi-GPU training, enterprise-grade security with audit logs, and full MLOps support with CI/CD pipelines.
How do I update AI Studio?
Users are made aware of updates through notices provided in the application. To update, navigate to Account > General > App Version to review release notes and update the software. Updates are also posted on ZDocs and on the Z by HP Data Science and AI Community. New features may require all collaborators to update to the latest version to take advantage of those features.
What data does AI Studio collect?
AI Studio collects account data for account management, application data (software version and installation status), contact data for account setup and validation, device data (CPU, storage, GPU utilization including cores/memory/clocks/temperature/power state, network utilization), feature usage data, location data for regional compliance, security credentials (tokens, not passwords), entitlement data for support tickets, and community engagement data. The platform does not collect demographic information, financial account information, social media account information, government-issued identifiers, or sensitive data like ethnic origin or health information.
How do I get started with HP AI Studio?
To get started, register on the platform and you'll receive an activation email from AI Studio with download links. Click the activation link, sign in with your HPID (or create one), download the installer for your platform (Windows or Linux), and follow the setup wizard. The new home screen provides access to tips, tricks, and helpful links, and an onboarding checklist walks you through creating a local deployment project from start to finish. You can then access the Data Science Stack Manager to select and install popular data science tools.