1. Order Management: Use image processing and OCR to facilitate order placements, payments, and tracking 2. Engagement: Track and guide the users through suggestions on workouts, meditation, nutrition, and overall health 3. Reminders: Help patients track their medication schedules through personalized reminders. Appointment management: Assist hospital staff schedule and manage appointments and bookings with ease 4. Customer support: Offer 24/7 customer support in over 55 languages across Website, App and even Whatsapp 5. Insights and Analytics: See your business critical data come to life through visually represented graphs and charts 6. AI-powered HR: Give more power to your people with AI-powered Employee Engagement, Learning and development 7. AI-powered ITSM: Improve organizational productivity by offering quick and easy resolutions to IT and Support queries and critical blackouts

Yellow Messenger is a Microsoft & SAP backed AI-based conversational platform that enables enterprises to automate conversations and trigger workflows directly through conversations without human intervention. Our automation layer can support intelligence on top of any communication channel (Whatsapp, MS team, Web etc) and integrate with customer’s existing Systems of Records and Systems of Engagements. The company specializes in the fields of artificial intelligence, customer engagement, customer service, chatbots, and enterprise. The company was founded in 2016 and is headquartered in Delaware, US.

Our AI-assisted labeling platform gives you to the tools to turn documents into data. Documents are automatically labeled, and you have the ability to adjust them and add your own. Annotate healthcare records, protocols, and papers more than 20x faster than manual labeling.

More than 80% of healthcare data is unstructured; it is either physical or in a digital format that requires manual labor to analyze, such as images or typed/handwritten notes. Healthcare runs on notes, scans, and PDFs. Because healthcare data is designed for manual labor, it cannot be easily searched, analyzed, or used to improve patients' quality of care or reduce cost of care. Manual labor does not scale, and the data is growing: 2 zettabytes of healthcare data are generated each year. Historically, the healthcare industry has invested in protocols for the structured data it has, digitizing analog data but leaving it unstructured, and brute-forcing the unstructured data problem through manual labor. These solutions have plateaued. We have to solve the unstructured data problem in healthcare. ScienceIO envisions a future where we enable all healthcare companies — across R&D, clinical trials, real world evidence, digital health, reimbursement, to care delivery — to learn from their data in real-time, so we can develop the next generation of healthcare solutions.