Specialized Services

GAVS’ specialized healthcare service offerings drive healthcare mobility through TeleHealth and can take your healthcare offerings to a whole new frontier with leading-edge AI solutions for life sciences.

Our TeleHealth solutions are backed by cloud enablement, desktop virtualization, device intelligence, connective tools, patient engagement apps, and patient 360 – a consolidated view of patient information. GAVS’ AI solutions for life sciences leverage the power of Machine Learning for areas such gene editing, genetic new-born screening, plasmid & chromosome identification, and chromosome prediction in human genomics.

Immersive Patient Experience through TeleHealth


Integrated & Bundled Apps with Microsoft Teams/Skype

Connective Tools for Advanced Specialty Treatment through Integrated Care (Cardiology, Endocrinology)


Microsoft Cloud for Healthcare - Resell & Implement

Cybersecurity Solutions for Data Security and Compliance to International Regulations and Standards


Patient Engagement Enhancements

Cognitive Chatbots & Physician Apps, Voice Recognition, Language Understanding for Foreign Language Patients, Emotional AI


Device Intelligence - Remote Monitoring & Maintenance

RMP through Interconnected Smart Devices, Predictable Device Uptime with ZIF Platform for Seamless, Timely Services and Elimination of Unwanted Costs


Patient 360 - Personal Health Records Integration with IoMT

Data Ingestion from Personal Health Devices and Link with Patient Profiles for Comprehensive Patient 360 and Subsequent Analytics



IP Solution for Secure Provider Access to Patient Data – Anytime, Anywhere and from Any Device

AI/ML-led Solutions for Life Sciences


Current and Future Applications

Gene Editing, Genome sequencing, Clinical Workflows, Consumer Genomics Products, Disease Prediction with Genomics, Pharmacy Genomics, Genetic New-born Screening


Clustering (Unsupervised learning)

Binning of Metagenomics Contigs, Identification of Plasmids & Chromosomes, Clustering Reads into Chromosomes for Better Assembly, Clustering of Reads as a Preprocessor for Assembly of Reads


Classification (Supervised learning)

Classifying Shorter Sequences into Classes (Phylum, Genus, Species), Phylogenetic Inference of the Sequences, Detection of Plasmids & Chromosomes, Finding Coding Regions, Chromosome Prediction in Human Genomics