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Research & Development

Advancing AI for Nepal & Beyond

Our R&D team works on real-world AI problems rooted in the Nepali context — low-resource NLP, Devanagari document intelligence, and AI for social good.

8+

Active Research Projects

3

Open Datasets Released

12+

Research Collaborators

6+

Publications / Reports

Research Focus

What We're Working On

Six core research tracks where HexCode Nepal is actively building, publishing, and contributing.

Large Language Models

Fine-tuning, RAG architectures, and low-resource LLM adaptation for Nepali language and domain-specific applications.

LLM Fine-tuningRAGNepali NLPPrompt Engineering

Nepali NLP

Building foundational NLP tools for the Nepali language — tokenizers, embeddings, sentiment analysis, and machine translation.

TokenizationEmbeddingsMachine TranslationNamed Entity Recognition

Computer Vision

Document digitization, OCR for Devanagari script, object detection for real-world Nepali use cases.

Devanagari OCRDocument AIObject DetectionImage Classification

AI for Social Good

Applying AI to healthcare screening, agriculture advisory, and disaster response in Nepal and the broader South Asian context.

Healthcare AIAgriTechDisaster ResponseLow-resource AI

MLOps & Deployment

Research into efficient model serving, edge deployment, and CI/CD pipelines for ML in resource-constrained environments.

Edge AIModel CompressionEfficient InferenceCI/CD for ML

Data & Benchmarks

Creating open datasets and benchmark suites for Nepali language and South Asian AI research.

Open DatasetsBenchmark CreationData AnnotationEvaluation
Publications

Recent Papers & Reports

Our team publishes findings from ongoing research to contribute to the broader AI community.

Devanagari OCR with Transformer-Based Architecture

Proceedings of Nepal AI Conference 2024 · HexCode Research Team · 2024

Low-Resource NLP for Nepali: Challenges and Approaches

South Asia NLP Workshop 2024 · HexCode Research Team · 2024

RAG Systems for Domain-Specific Knowledge in Nepal's Public Sector

Internal Technical Report · HexCode Research Team · 2025

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