We Make Open-Source LLMsAccessibleAffordableReliable
For Every Enterprise
An integrated platform to fine-tune, deploy and manage LLM applications
An integrated platform to fine-tune, deploy and manage LLM applications
Tensormatrix excels in efficient LoRA-based LLM fine-tuning, setting a new benchmark in the industry
Our approach allows for fine-tuning of LLMs with just 1/10th the GPU usage compared to PEFT automatically
This significant reduction in resource requirements enables us to tailor these models to specific use-cases and industries more cost-effectively
Our model serving solutions are uniquely designed to utilize both CPU and GPU memory concurrently
This innovative approach significantly reduces operational costs by more than 80%, offering a highly economical option for businesses seeking advanced AI capabilities
Offer various LLM model serving frameworks and efficient GPU memory management strategies
Fault Tolerance
Distributed training can continue to operate in the event of a failure
Flash Checkpoint
Distributed training can recover from failures within seconds from memory checkpoints
Automatic Scaling
Distributed training can scale resources up or down to improve stability, throughput, and resource utilization
M-LoRA
Effecient LLM model fine-tuning
DLRover
An Automatic Distributed Deep Learning System
Couler
Automatically AI workflow management
Construct an LLM-based data pipeline to extract network maintenance commands
Develop a multi-role AI agent to analyze IT network errors and suggest solutions
Conduct IT QA report analysis and summarize user satisfaction
Extract the patent knowledge tree using a fine-tuned LLM
Assess the novelty of the patent using an AI agent and the patent tree
Merge in-store patent data and web information to create a patent development report with LLM
Use an agent to schedule appointments and analyze patients' conditions
Provide initial suggestions for basic patient issues
Conduct follow-ups on patients' conditions post-hospital visit
Utilize a fine-tuned LLM model to convert text into SQL for data interpretation
Offer advanced data analysis leveraging LLM
Develop an ML pipeline to forecast future gas market fluctuations based on the LLM-recommended workflow