Training and evaluating advanced machine learning models requires access to high-quality, tailored, multimodal datasets, which are often limited or unavailable. This scarcity hinders the development of accurate and reliable AI models, particularly for specialized applications.

Bespoke Labs addresses the data bottleneck in AI development by providing tools for creating synthetic datasets and fine-tuning specialized models using generative AI. Their platform enables engineers to curate high-quality, multimodal datasets tailored to their specific needs, improving the precision and performance of their models. Bespoke Labs focuses on data curation and post-training techniques to enhance model reasoning and tool use. The company's research-driven approach keeps them at the forefront of new tools and insights in the field of AI data curation.

Curator: Tool for creating synthetic datasets with speed and modularity

Evalchemy: A unified platform for large language model (LLM) evaluation

Minicheck 7B: A state-of-the-art hallucination detection model

OpenThinker models: Reasoning models with open data, designed for political decensoring

Reinforcement learning (RL) techniques for improving multi-turn tool use in AI agents

Bespoke-MiniChart-7B: A chart understanding model that analyzes complex charts and infographics

Tools for post-training LLMs

Bespoke Labs targets AI engineers and researchers who require tailored, high-quality datasets for fine-tuning and evaluating machine learning models, as well as organizations seeking to improve the reasoning and tool-use capabilities of their AI agents.