Pandan Labs builds the tools and infrastructure to turn open AI models into specialized, deployable AI services.
We work across the model lifecycle—from dataset preparation, fine-tuning and evaluation to inference optimization, deployment and API delivery.
Our focus is making AI practical for specific languages, industries and real-world workflows, particularly where general-purpose models and existing infrastructure fall short.
We adapt, fine-tune and evaluate open models for specialized tasks, languages and industry domains. Our work includes dataset preparation, synthetic data generation, benchmarking, model optimization and reproducible training pipelines.
We package and deploy models for efficient, reliable inference across different compute environments. This includes model serving, versioning, deployment automation, performance optimization and operational monitoring.
Our GPU compute and inference platform connects models with the infrastructure needed to run them. It provides a foundation for managed APIs, dedicated inference endpoints and deployments across multiple GPU providers.
| Type | What's there |
|---|---|
| Models | Specialized and fine-tuned models, including OCR, speech, language and domain-specific AI. |
| Datasets | Curated datasets, synthetic training resources, evaluation benchmarks and ground-truth collections. |
| Spaces | Interactive demonstrations, model comparisons and experimental applications. |
| Tools | Open-source utilities for model preparation, evaluation, optimization and deployment. |
Our initial work includes classical Arabic document understanding and OCR, Bangla language processing, and specialized models for regional and industry-specific applications.
These are starting points for a broader effort to make model specialization and production inference more accessible, reproducible and economical.
From models and datasets to production-ready AI services.
Contact: hello@pandanlabs.ai