Waiv offers AI-powered precision tests that automatically analyze digital pathology slides to extract morphological and molecular biomarkers, delivering fast, quantitative reports for outcome prediction and treatment-response assessment. The cloud-based platform integrates with existing pathology and laboratory information systems via standard APIs, enabling high‑throughput, scalable biomarker analysis for diagnostic labs and pharmaceutical partners.
Funding
Funding not disclosed
Founders
Product
Problem
Oncologists and diagnostic labs face increasing complexity and cost in biomarker testing, requiring analysis of high‑dimensional digital pathology data that exceeds manual interpretation capacity. This hampers timely biomarker discovery, outcome prediction, and treatment‑response assessment needed for precision oncology.
Solution
Waiv provides AI‑powered precision tests that automatically analyze digital pathology slides to extract morphological and molecular biomarkers. Their platform leverages a large, multi‑institutional dataset and clinically validated models to deliver fast, accurate results that integrate into existing diagnostic workflows. By automating high‑dimensional data analysis, Waiv enables scalable biomarker discovery, outcome prediction, and treatment‑response assessment across oncology. The solution supports multimodal diagnostic pipelines, allowing healthcare providers to incorporate AI insights alongside traditional pathology and molecular testing. Waiv collaborates with pharmaceutical companies, research institutions, and diagnostic organizations to ensure the tests meet clinical standards and accelerate precision‑medicine adoption.
Target Audience
Primary customers are oncology diagnostic laboratories, hospital pathology departments, and pharmaceutical partners developing companion diagnostics who require high‑throughput, AI‑enhanced biomarker analysis.
Features
- AI models trained on a diverse, international dataset of digital pathology slides, ensuring robust performance across tumor types and populations
- Automated extraction of quantitative morphological features for biomarker discovery and validation
- Integrated outcome‑prediction and treatment‑response assessment modules that generate clinically actionable reports
- Seamless integration with existing digital pathology and laboratory information systems via standard APIs
- Scalable cloud‑based processing pipeline delivering rapid turnaround times for high‑throughput clinical settings
- Ongoing model validation and regulatory compliance to support clinical deployment