Research
Research focussed development of Ayurveda healthcare's future.
Exploring how artificial intelligence, medical technology, healthcare data and computational methods can strengthen evidence-building in Ayurveda.
Research & Development Areas
Research Domains
PramAnA's research and development spans multiple intersecting domains. Development stage, validation status and intended use vary by area.
Clinical Outcome Measurement
Developing methods and tools for structured measurement and documentation of clinical outcomes in Ayurveda practice.
Medical Technology & Sensors
Exploring non-invasive sensing and measurement technologies for capturing Ayurveda clinical parameters.
Artificial Intelligence
Applying machine learning, deep learning and AI reasoning to Ayurveda clinical data and knowledge.
Computer Vision & Imaging
Developing intelligent imaging and visual analysis methods for Ayurveda clinical assessment.
Ayurveda Knowledge Representation
Structuring Ayurvedic clinical knowledge into computable, machine-readable formats for AI systems.
Knowledge Graphs & RAG
Building knowledge graph architectures and retrieval-augmented generation systems for Ayurveda intelligence.
Healthcare Data
Developing frameworks for structuring, standardising and analysing Ayurveda healthcare datasets.
AI-Assisted Drug Discovery
Exploring computational approaches to Ayurveda pharmacology and drug discovery research.
Research & Development Approach
From Observation to Translation
PramAnA's research and development follows a structured approach — from clinical observation through to technology translation. Not every stage has been completed across all research areas.
Observe
Clinical observation and problem identification in Ayurveda practice
Capture
Structured data capture from clinical and sensing systems
Structure
Data structuring, standardisation and knowledge representation
Understand
Pattern recognition, analysis and clinical insight extraction
Model
AI model development and knowledge graph construction
Validate
Clinical and technical validation of models and outputs
Translate
Translation of research into clinical tools and healthcare technology
Publications & Research
Publications & Research
PramAnA's research explores the intersection of Ayurveda, artificial intelligence, computational knowledge representation and healthcare technology.
01
Venue
2025 1st International Conference on Smart and Intelligent Systems (SISCON)
Publisher
IEEE
Year / Pages
2025 · 1–6
DOI
10.1109/SISCON66686.2025.11409308
IEEE Xplore
Retrieval-Augmented Generation and Knowledge Graphs for Intelligent Ayurvedic Chatbots
S. Supal, S. M. Anzar, C. P. Sankar & O. V. Abhilash
This work presents a hybrid intelligent Ayurvedic chatbot architecture combining Retrieval-Augmented Generation with Knowledge Graph reasoning. The system integrates semantic vector retrieval with structured Ayurvedic knowledge representation to generate context-aware responses grounded in Ayurvedic source knowledge.
02
Venue
Abhinava Dhanvantari Journal of Ayurveda
Publisher
Abhinava Dhanvantari Journal of Ayurveda
Year / Pages
2025 · 14th Issue, August–December 2025
Journal
From Siddhānta to System: Computational Foundations for Artificial Intelligence in Ayurveda
Dr O. V. Abhilash & Dr Arya Krishnan
This paper explores the computational foundations for applying Artificial Intelligence to Ayurveda by examining how Ayurvedic Siddhāntas can be represented through algorithmic, knowledge-centric and heuristic approaches. It examines the relationship between Ayurvedic clinical reasoning and computational models, including knowledge graphs, causal reasoning and domain-specific learning systems. The paper proposes that Ayurveda-specific AI should preserve the contextual, epistemological and experiential dimensions of Ayurvedic reasoning while using modern computational methods to improve interpretability, consistency and scalability.
From Knowledge to Intelligence
From Knowledge to Intelligence
These research directions contribute to a broader exploration of how Ayurveda knowledge can be represented, retrieved, reasoned over and translated into intelligent healthcare systems.
Ayurveda Siddhānta
Computational Representation
Knowledge Graphs
RAG / AI Models
Clinical Intelligence
Research Principles
How We Research
Clinically Relevant
Research grounded in real clinical problems and Ayurveda practice.
Data-Driven
Evidence built on structured data, measurement and analysis.
Ayurveda-Centric
Technology that preserves and respects Ayurvedic epistemology.
AI-Assisted
Intelligent systems that augment clinical knowledge and reasoning.
Evidence-Oriented
Rigorous, peer-reviewable and clinician-validated research.
Technologies and research described on this website represent ongoing development and exploration. Development stage, validation status and intended use may vary by technology.
Collaborate on Research.
We are looking to collaborate with clinicians, researchers, academic institutions and healthcare technology organisations.