Peak platform architecture across the AI Platform and application layers, with a description of modules for infrastructure, data management, and application development.

Peak is organized across two layers: AI Platform for infrastructure and data management, and another layer for application development and deployment. This page describes the modules available on each layer.

The AI Platform layer provides services for managing data, configuring integrations, and controlling access. Platform administrators, IT teams, and data teams use these modules to enable Peak products and solutions.

Connect to business systems using standard connectors to common databases and SaaS applications. Peak also provides a data ingestion API for direct integration of existing business applications and Peak products.

Manage user and team access to Peak products using role-based access control. Define which users can access specific Peak products and features based on their organizational roles.

Connect to your existing Redshift or Snowflake data warehouse to bring data into Peak. Data Bridge enables secure integration with Peak's products and solutions.

Discover and deploy tools and business applications from Peak's product catalog. Manage deployed products and roll out upgrades.

Store and manage structured and unstructured data on Peak. Upload, download, and preview data such as reports and datasets using Peak's Files.

Use Autopilot, an AI-powered assistant, to onboard to Peak, debug issues, and chat with your data and interact with Peak's AI outputs.

This layer provides tools for building, training, testing, and deploying AI applications and automation. Developers, data scientists, and AI engineers use these modules to develop solutions on Peak. Tge layer requires a data warehouse to connect to. You can either:

Access cloud-based data and machine learning development environments with direct connectivity to Peak data sources. Choose from Jupyter Lab or RStudio workspaces. Remote tunneling access is available upon request.

Create and manage data and machine learning pipelines and automation tasks. Configure elastic compute options, notifications, alerting, conditional logic, and parameterization for pipeline orchestration.

Deploy and manage web applications, data visualizations, and model APIs. Configure elastic compute, connectivity, session management, and scaling rules for data and memory-intensive applications.

Track model experiments and performance using Peak's MLFlow implementation. Annotate experiments and model training outputs with performance metadata and plots.

Create and manage development environments for your data and machine learning workloads. Use preset images or define custom images, manage versions, and deploy secrets securely.

Build and manage AI applications using Press, Peak's AI application development toolkit. Automate deployments and update rollouts. Use composability features to swap data and machine learning components across projects.

Contact your UiPath representative to add optional modules to your subscription.

Explore business data using Peak's SQL editor and query engine. Visualize data using integrated BI dashboarding tools.

Connect to enterprise SaaS applications including Salesforce and SAP. Contact your UiPath representative for the list of available Premium Connectors.

Have Peak provision and manage your Snowflake or Redshift Data Warehouse. Warehouse size, instance size, and number of warehouses or nodes are determined through discussion with Peak technical sales representatives.