AutoLabelling for LLMs
Streamline the preparation and deployment of labeled datasets for fine-tuning and deploying Large Language Models (LLMs).
How do businesses use Casp AI?
Processing Any Kind of Documents
Automate the segmentation and structuring of diverse document types, including images, PDFs, audios, and videos. Simplify the preparation of unstructured data for improved consistency and usability.
Automatic Paraphrasing and Labelling Conversations
Accelerate dataset creation with automated paraphrasing and labeling for conversations. Enhance model training by assigning meaningful tags and context markers, compatible with open-source and custom LLMs.
Generic LLM Finetuning Methods
Standardize fine-tuning approaches for models like GPT, Google Gemini, and NVIDIA LLAMA. Optimize LLMs for conversational, domain-specific, or computational linguistics tasks efficiently.
Deploy in Private Endpoints, Private Hostings, and Inference Servers
Simplify deployment with secure hosting options. Use private endpoints, dedicated servers, or inference servers for real-time model interactions with minimal latency and enterprise-grade privacy.
End-to-End Data and Model Preparation
Streamline the entire process from dataset preparation to model deployment. Ensure secure, scalable, and efficient workflows tailored to business-specific needs.