Enterprise AI Solutions
Unlock Precision in Histopathology with AI Agents
Our cutting-edge framework, NOVA, automates complex histopathology analysis, accelerating discovery and improving diagnostic accuracy.
Executive Impact
NOVA delivers tangible benefits, transforming research workflows and enhancing decision-making in computational pathology.
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
NOVA Framework Overview
NOVA is an agentic framework designed for automated histopathology analysis and discovery. It translates scientific queries into executable analysis pipelines by iteratively generating and running Python code. Integrating 49 domain-specific tools, NOVA supports dynamic, interactive, and dataset-level scientific discovery without instruction-fine-tuned models.
Enterprise Process Flow
Performance Insights on SLIDEQUEST
NOVA significantly outperforms coding-agent baselines on SLIDEQUEST, a 90-question benchmark verified by pathologists. This highlights the necessity of structured tool use and iterative coding for complex computational pathology tasks.
The benchmark spans DataQA, CellularQA, PatchQA, and SlideQA categories, demanding multi-step reasoning, iterative coding, and computational problem solving. While DataQA scores are high, CellularQA and SlideQA still present significant challenges, indicating areas for future tool refinement.
| Category | LLM Only | LLM + PI | LLM + PI + Retries | NOVA |
|---|---|---|---|---|
| DataQA | 0.000 | 0.377 | 0.443 | 0.777 |
| CellularQA | 0.000 | 0.058 | 0.152 | 0.323 |
| PatchQA | 0.000 | 0.039 | 0.217 | 0.335 |
| SlideQA | 0.000 | 0.133 | 0.259 | 0.472 |
| Overall | 0.000 | 0.154 | 0.269 | 0.477 |
Case Study: PAM50 Subtype Morphological Features Exploration
NOVA successfully explored the morphological features associated with PAM50 breast cancer subtypes (Luminal A, Luminal B, Basal-like, HER2-enriched) and assessed their relationship with tumour characteristics. This pathologist-verified case study demonstrates NOVA's scalable discovery potential by integrating multiple tools and biological knowledge to derive insights.
Key Findings:
- Luminal A: Low nuclear grade, well-formed tubules, minimal necrosis, reflecting an indolent nature.
- Basal-like: High nuclear grade, high mitotic rate, central necrosis, extensive inflammation, indicative of aggressive behavior.
- HER2-enriched: High nuclear grade, frequent comedo-type necrosis, solid growth pattern, also pointing to aggressive behavior.
Outcome: The detected morphological features and cell segmentation results were coherent with known biology and clinical behavior, providing insights that can inform prognosis and guide treatment decisions in breast cancer management.
Calculate Your Potential Impact
Estimate the efficiency gains and cost savings by automating your histopathology analysis workflows with AI.
Your AI Implementation Roadmap
A clear path to integrating NOVA into your existing research and diagnostic workflows.
Phase 1: Discovery & Strategy
Initial consultation to understand your specific needs, data modalities, and integration requirements. Define key objectives and success metrics.
Phase 2: Custom Tooling & Integration
Develop custom tools for your unique tasks, integrate with your data infrastructure, and set up the agentic framework tailored to your environment.
Phase 3: Validation & Deployment
Rigorously test the deployed system on your data, validate results against ground truth, and ensure seamless operation within your enterprise systems.
Phase 4: Ongoing Optimization & Support
Continuous monitoring, performance optimization, and dedicated support to ensure your AI agent delivers sustained value and adapts to evolving needs.
Ready to Transform Your Research?
Connect with our AI specialists to explore how NOVA can revolutionize your histopathology analysis and discovery.