Xavo Enterprise

Xavo Enterprise is a sample management platform designed for labs that require advanced automation, configurable workflows, and real-time device coordination at scale. It is positioned as the most complete tier in the Xavo product line, building on the capabilities of Xavo Professional by adding low-code process modeling, detailed equipment representation, automated storage integration, configurable business rules, and an algorithmic scheduling engine.

The platform is intended for labs with complex, high-throughput operations — such as NGS preparation, compound distribution, or multi-device automation landscapes — where workflows need to be digitized precisely according to existing SOPs and physical infrastructure, rather than adapted to simplified templates.

Core Capabilities Inherited from Xavo Professional

• Complete sample management and inventory tracking
• Storage occupation control
• Structured order creation and execution

Modeled Lab Processes

• Supports digitization of lab workflows in full detail, aligned with SOPs, business logic, and physical infrastructure
• Accommodates multi-step processes such as NGS prep or compound distribution cascades
• Reflects real-world protocols rather than simplified workflow templates

Detailed Lab Device Representation

• Represents equipment digitally, including deck layouts, plate formats, container compatibilities, and transfer constraints
• Enables accurate calculation of liquid volumes, pipetting strategies, and storage logistics
• Treats liquid handlers (e.g., Tecan, Hamilton) as fully understood components within the operational data model, not merely connected peripherals

Integrated Automated Storage

• Integrates with automated storage systems from vendors including Azenta, Hamilton, and SPT
• Handles sample retrieval, loading, and capacity management
• Issues pick requests, monitors status, and triggers downstream processes when materials arrive

Configurable Lab Rules and Execution Logic

• Supports configuration of detailed business rules governing how and when tasks are performed
• Enforces naming conventions and labeling strategies automatically
• Defines fallback strategies when containers are unavailable
• Specifies handling of partial volumes
• Ensures operators and robots follow correct execution paths without manual decision-making or template setup

Lab Automation Orchestration

• Acts as a central coordination layer for liquid handlers, storage systems, mobile robots, and manual tasks across vendors and technologies
• Understands the context of each order and delivers device-specific instructions in the correct format at the appropriate time
• Supports both high-throughput batch workflows and just-in-time execution

Dynamic Deliverable and Instruction Calculation

• Calculates all task requirements in real time when a request is placed, including intermediate plates, transfer and dilution volumes, and container type selection
• Optimizes transfers based on deck positions
• Generates machine-readable instructions for devices such as liquid handlers
• Supports on-demand execution in environments with variable inventory and shifting priorities

Resource Coordination and Scheduling

• Includes an algorithmic and AI-assisted scheduling engine that coordinates lab activities across instruments
• Assigns, sequences, and executes tasks to maximize throughput and minimize idle time and conflicts
• Supports both batch protocols and complex multi-device workflows

Technical Architecture

• Cloud-native platform with containerized applications, Kubernetes-orchestrated and hosted on Amazon Web Services (AWS) as a single-tenant deployment
• Multi-user system with optional Single Sign-On (SSO) integration
• Multi-tier, distributed architecture supporting elastic horizontal and vertical scaling
• Integration-ready with external systems and lab equipment via IoT agents and UI

Xavo Enterprise is deployed as a cloud-native, single-tenant solution on AWS, and supports integration with existing enterprise systems through SSO and IoT-based connectivity. The scheduling engine component is noted as part of a supported project, indicating ongoing development in AI-assisted lab planning.