Here's why clients choose us
Pathogenic variants ranked in first positions
Classification accuracy up to 98%
VUS reduction up to 60%
Intuitive and Fast
Secure and CE IVD marked
Excellence in monogenic interpretation
Winner of the NIH-funded CAGI6 Challenge, eVai platform automates ACMG guidelines and prioritizes variants to highlight candidate diagnoses.
- Automated ACMG Classification
eVai automatically pre-classifies SNV, Indels and CNVs and ranks them according to a hypothesis-free approach. The classification is disease-specific and reports both the activated criteria and the supporting evidence.
- AI-powered Suggested Diagnosis
eVai leverages a proprietary AI technology that exploits variant pathogenicity together with patient phenotypes and family information to suggest the most likely genetic diagnosis for the patient.
Digenic and Oligogenic Interpretation
Our Suggested Diagnosis can predict digenic and oligogenic combinations based on a rigorously evaluated and benchmarked model. Users can explore candidate pairs and the supporting literature if available.
Laboratory Knowledgebase
Variant-disease associations can be submitted to a private lab repository that can contribute to significantly improve classification and prioritization performances over time. Moreover, the lab repository can be used to store info about variant artifacts.
- Family Analysis
Analyze trio, quartet or up to 7 family members: for each variant, eVai will automatically infer the possible inheritance patterns according to a fully penetrant disease. Users can select the variants that fit certain inheritance patterns and quickly compare genotypes across the members.
- Variant Filtering
eVai enables users to create virtual gene panels and custom variant filters by leveraging on multiple omics resources such as Human Phenotype Ontology.
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Make your interpretation process intuitive, faster and more accurate.
eVai guarantees the highest level of security, privacy and quality and is CE IVD-certified
Trusted worldwide
VarChat is the first open platform to use Generative AI for searching genomic variants in literature and synthesizing information in a coherent and concise way.
Publications
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Discover how our data-driven prioritization approach could be essential to ease and support variant interpretation in clinical settings by suggesting which uncertain variants may have a higher probability of pathogenicity.
Discover how eVai improved variant pathogenicity assessment for cardiovascular related genes.
Success stories
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Success stories
Enabling accurate and fast variant analysis for the diagnosis of genetic diseases causing hearing loss
14 July 2020
Success stories
The benefits of hypothesis-free interpretation to solve undiagnosed cases
23 December 2019
Success stories
Lung and colorectal cancer variant prioritization at Kabara Cancer Research Institute
29 July 2019