Bridging Himalayan roots with global scale intelligence.
DAIR Unit is Dignep’s applied research wing focused on building trustworthy, high-impact AI systems for industry, society, and public good grounded in Nepal and connected to the world.
AI Research, Engineered for the Global South
DAIR is the corporate R&D arm of Dignep Group, focused on applied AI research and industrial-grade AI products that transform businesses, public services, and human wellbeing. We advance state-of-the-art methods in machine learning, multimodal perception, optimization, and trustworthy AI and move results from prototypes to production at scale.
“DAIR delivers university grade research rigor with startup speed delivery.”-Dr. Yagya Raj Pandeya (Head, DAIR)
DAIR’s research is structured around six applied pillars, each addressing a critical gap between AI theory and human reality:
Generative AI and Multilingual Foundation Models
Low-resource NLP for Nepali and regional languages; translation, instruction tuning, and domain adaptation.
Retrieval-Augmented Generation (RAG) for factual, latency-conscious assistants, Safety tooling: hallucination detection, red-teaming, preference alignment.
Affective Computing and Human Centered AI
Emotion recognition from audio, video, and text robust to noisy, real-world data.
Behavioral signal analysis (gaze, micro-expressions, prosody) for well-being, education, and CX.
Privacy-preserving designs and bias assessment across demographics.
Multimodal Learning and Fusion
Efficient multimodal architectures, self-supervised pretraining, and domain-specific models (medical, aerial, agricultural).
High-dimensional optimization and compression for edge deployment.
Smart Systems and Edge AI
On-device intelligence with quantization, pruning, and privacy-aware inference.
Sensing + IoT stacks for monitoring, traceability, and infrastructure health.
Decision intelligence combining ML with rule-based systems.
AI Governance, Safety, and Policy Enablement
Contextual risk matrices, threat modeling, model cards, system cards, and audit trails.
Policy research and tooling for responsible public sector deployment.
Applied AI for Social Impact
Problem-driven AI for healthcare, agriculture, education, disaster response, and governance.
Co-design with communities and local partners to ensure inclusivity and practicality.
Mission
In the last decade, humanity has built machines that can think, speak, and create. But not understand.
The first generation of AI optimized for prediction not perception. For speed not sense. For outputs not outcomes.
At DAIR, we believe it’s time for a deeper shift: from artificial intelligence to authentic intelligence systems that learn, adapt, and align with human values and local realities.
Origin Story
DAIR was founded within Dignep Group innovation engine as a bridge between academic excellence and real-world application.
Led by Assistant Professor Yagya Raj Pandeya from Kathmandu University’s Department of Artificial Intelligence, DAIR brings over a decade of experience in deep learning, multimodal data fusion, and affective computing.
It unites researchers, engineers, and industry partners across Nepal and beyond to build AI systems that are as ethically aware as they are technically advanced.
Our Philosophy Conscious AI
AI must not just think for humans. It must think with humans.
Conscious Intelligence is our guiding paradigm.
It rests on three principles:
Local Context is Global Relevance
Intelligence that ignores geography becomes ideology.
Nepal’s social, linguistic, and infrastructural diversity offers an ideal testbed for globally scalable AI models.
Ethics is Architecture, Not Afterthought
Governance must be coded into the system, not bolted on as policy.
Our goal is to make ethical AI as default as data itself.
Science Must Be Open, Not Opaque
DAIR commits to open-source principles releasing frameworks, datasets, and benchmarks for community use.
Progress must be a public good.
Why a DAIR Corporate Unit?
Speed with Rigor: We pair academic excellence with product engineering rigor turning validated research into real services on accelerated timelines.
Local Roots, Global Standards: Rooted in Nepal’s talent and perspectives; delivering systems that meet international benchmarks for accuracy, safety, and maintainability.
End-to-End Ownership: From data collection and model research to MLOps, compliance, and monitoring, DAIR owns the full lifecycle.
Commercial Alignment: Research is prioritized by measurable business KPIs.
Leadership
Dr. Yagya Raj Pandeya, Ph.D. | Assistant Professor, Department of Artificial Intelligence, School of Engineering, Kathmandu University | (Head, DAIR).
Dr. Yagya Raj Pandeya is a leading Artificial Intelligence (AI) expert and national policy driver for Nepal. With a Ph.D. and Postdoctoral Research in AI from Jeonbuk National University, South Korea, he brings extensive global expertise.
As an Assistant Professor at Kathmandu University, Department of Artificial Intelligence, he leads the Artificial Intelligence and Smart System Research (AISSR) laboratory, focusing on critical real-world applications of AI in agriculture, healthcare, disaster management, and cultural preservation.
A prolific author, Dr. Pandeya is also a key member of Nepal’s National AI Policy (2081) and a team leader for the National AI Strategy (2082), Recently published by the Government of Nepal.
Partnerships and Programs
Industry collaborations
We partner with startups, enterprises, and public sector organizations to co-develop AI solutions aligned with sector needs and constraints.
- Sponsored Research: Define a problem statement and co-drive a research roadmap with measurable outcomes.
- Joint Development: From research prototype to production-ready systems (APIs, microservices, dashboards).
- Pilots and Deployments: Controlled rollouts, monitoring, and continuous improvement with safety and governance built in.
Academic collaborations
- Joint Projects and Co-supervision: Work with faculty and students across departments on shared research goals.
- Exchange and Residencies: Visiting researcher programs; sabbatical engagements; Unit exchanges.
- Shared Resources: Datasets, benchmarks, compute resources, and evaluation harnesses for regional problems.
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