PuzzleOmni
An operating-system-level architecture for AI-enabled pathology departments, integrating data governance, R&D, tool deployment, and computer-aided diagnosis into a closed loop that enables pathology data and AI assets to flow intelligently from production to application.
- End-to-end workflows: unified management of data, models, tasks, and inference
- Traceable human-in-the-loop workflow: annotation review, logging, and process replay
- Large and small model synergy: multimodal training and agent-based reasoning
Data Governance
Unified management of multi-source pathology data, with standardized processing and intelligent search to establish a high-quality data foundation.
Research & Development
Providing convenient model training, validation and publishing environments to accelerate AI algorithm iteration and innovation.
Tool Deployment
Encapsulates AI capabilities as services for flexible deployment across application scenarios, accelerating practical adoption.
Assisted Diagnosis
Real-time, intelligent diagnostic support for pathologists to improve diagnostic efficiency and accuracy.
Core Value for Pathology
Key capabilities for improving efficiency across the entire pathology workflow
Efficiency Gains and Workload Reduction
AI-assisted slide review and automated structured report generation substantially reduce repetitive work, enabling pathologists to focus on complex case diagnosis.
Research Efficiency and Quality
Standardized data management and convenient model-training tools accelerate research projects and output; built-in AI agents autonomously orchestrate tools, invoke models, optimize workflows, and continuously learn and evolve.
Data and AI Asset Management
Organizes hospital data and knowledge resources, builds and manages AI assets, and supports AI-assisted diagnostic services inside and outside the hospital.
Core Positioning
A General-purpose AI Operating System in Pathology
Resource Manager and Interfaces
Data Governance
AI-assisted data collection and search through PIS integration, with dataset import and conversion into standard formats for data construction.
Access Control
Unified management of model tools through the model platform, with connections to scanners and server clusters through hardware interfaces.
Workflow and Compute Engine
Model Training
AI-assisted training of both large and small models using local data.
MCP Deployment
Unified scheduling of large and small model tools, deployed as API tools or agents.
Smart Assistant
A native system-level AI assistant for research and application workflows.
Application and Interaction Platform
PuzzleSeg Slide Viewer
Advanced interaction design and modular AI tool deployment, using trained models for assisted diagnosis.
PuzzleAgent Report System
Advanced agent tools and leading interaction design, supporting modular AI deployment and creating explainable, interactive, and traceable end-to-end workflows.
More Application Tools
Continuously expands the application ecosystem to cover more pathology scenarios.
Resource Manager and Interfaces
Workflow and Compute Engine
Application and Interaction Platform
Data Governance
AI-assisted data collection and search through PIS integration, with dataset import and conversion into standard formats for data construction.
Model Training
AI-assisted training of both large and small models using local data.
PuzzleSeg Slide Viewer
Advanced interaction design and modular AI tool deployment, using trained models for assisted diagnosis.
Access Control
Unified management of model tools through the model platform, with connections to scanners and server clusters through hardware interfaces.
MCP Deployment
Unified scheduling of large and small model tools, deployed as API tools or agents.
PuzzleAgent Report System
Advanced agent tools and leading interaction design, supporting modular AI deployment and creating explainable, interactive, and traceable end-to-end workflows.
Smart Assistant
A native system-level AI assistant for research and application workflows.
More Application Tools
Continuously expands the application ecosystem to cover more pathology scenarios.
Four Core Highlights
Comprehensive capabilities spanning research, model training, agent systems, and system integration
AI Ideas
Research & system navigation
Closes the loop from data collection to model inference
From data collection to inference loop
Supports agent configuration and collaborative execution
Agent configuration & collaborative execution
Supports platform deployment and continuous operations
Platform deployment & continuous operations
Closed-Loop Flywheel from Data to Diagnostic Support
Builds a continuous feedback loop in which data, models, and applications reinforce one another
Intelligent Data Governance
After integration with PIS, the intelligent assistant helps import datasets and convert them into standard formats
Interactive Model Training
Supports AI-assisted training of large and small models using local data
AI Service Management
Supports compute deployment for model services and unified management of data resources
Intelligent Assisted Diagnosis
Deploys trained models as modular components in the AI slide viewer for assisted diagnosis and data annotation
Business feedback continuously flows back to data governance and model training stages, forming a self-reinforcing "data-model-application" cycle.
Layered System Architecture
Three-layer coordination across the application layer, AI service layer, and system layer to provide end-to-end, production-grade support.
Platform Application Layer
AI & Integration Service Layer
Infrastructure Service Layer
PuzzleOmni provides end-to-end production support through coordinated application, AI service, and system layers.
FAQ
Start Building Your Digital Pathology Platform
Tell us about your use case and we'll provide a customized implementation plan
Content on this page is for product capability introduction and does not constitute medical diagnostic advice