Archive · 31 Jan 2026
CCRAS Concludes AI Internship in Ayush Sector
The Central Council for Research in Ayurvedic Sciences (CCRAS) recently finished a special training program where students learned how to use computers and smart technology to help with traditional Indian medicine, called Ayush.
This program ran from mid-December to the end of January.
Many students applied, but only 33 were chosen.
These students worked on different projects, like using computers to study plants, understand health types (Prakriti), and even read old handwritten documents.
The goal was to make Ayush medicine stronger by using modern technology.
The leaders at CCRAS are happy with the results and want these projects to be tested and used more in the future.
They believe this will help make Ayush medicine more popular and trusted.
CCRAS concluded an AI internship program in Ayush systems from December 15 to January 30.
180 applications were received, with 33 interns selected for the program.
Interns worked on AI projects in medicinal plant research, bioinformatics, Prakriti assessment, medical imaging, posture detection, and OCR of manuscripts.
The program aimed to strengthen IT and data-driven approaches in Ayush research.
CCRAS plans to validate and scale the developed applications for broader implementation.
- Who
- Central Council for Research in Ayurvedic Sciences (CCRAS) and 33 selected interns
- What
- Concluded an internship program on AI in Ayush systems
- When
- December 15 to January 30
- Where
- India (specific location not mentioned)
- Why
- To strengthen the application of IT and data-driven approaches in Ayush research
- Organizer
- Central Council for Research in Ayurvedic Sciences (CCRAS)
- Program Duration
- December 15 to January 30
- Applications Received
- 180
- Interns Selected
- 33
- Focus Areas
- Medicinal plant research, bioinformatics, Prakriti assessment, medical imaging, posture detection, OCR of manuscripts
- Objective
- Strengthen IT and data-driven approaches in Ayush research
- Outcome
- Development of AI-enabled projects for validation and scaling