Differentiate

AI/ML powered solutions

Differentiate your brand experience with the power of AI and ML

Why?

Based on the fundamental understanding of human cognitive function, Artificial Intelligence is bringing a paradigm shift to healthcare , owing to the availability of electronic data (structured or unstructured). Disease areas that use AI tools include cancer, neurology, and cardiology. Available AI applications are already bringing tremendous value in early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation in stroke. A study published in BMJ 2017 discusses the past, present, and future of AI in healthcare (1). AI and ML is the future of healthcare- at no stage of evolution we will ever be able to meet the healthcare needs of ever-growing global population, AI, and ML can truly help us to be future-ready. For any brand adapting the AI/ML solutions is of prime importance as it will not only make your business productive but it will differentiate you from your competitors.

How?

We do have our in-house AI-based solutions that are solving common problems for businesses, one of our solutions helps the manufacturers and hospitals to save electricity with the help of AI-based continuous monitoring. With extensive research at our end, we identify the global trends in AI and ML and suggest it to our clients the possibility in creating a differentiator with the use of AI and ML in their business. We also build a custom algorithm for our clients, for all the innovation including sharing the patents with our clients.

Who?

AI and ML solutions can be adopted by all the healthcare organizations who have the availability of their data in the electronic or digital format. Clients who are looking at creating differentiators with the help of automation also save cost and efforts.

When?

The best time to create a differentiator is now!

What?

Our AI/ML-based solutions include but not limited to: Automated Medical Transcription using NLP, Suggestive Diagnosis using Sequence Modelling, Medical Image Detection and Classification, Spend Analytics and Cost Optimization, Capacity Planning and Consumer Analytics, Assembly line optimization, Device Failure Prognostics.

  1. Jiang F, Jiang Y, Zhi H, et alArtificial intelligence in healthcare: past, present and futureStroke and Vascular Neurology 2017;2:doi: 10.1136/svn-2017-000101