Enterprise SLM Platform
Unleash the power of the Small Langauge Model to convert your static information into a knowledge base. Safeguard and protect your information while harnessing the power of Generative AI to understand and process data at a fraction of the cost
Platform features
Designed for private cloud and on-prem use case tailored towards businesses and large organization
Use the command-line interface to create projects, upload assets, and test models, making it ideal for development teams to move quickly
Fully managed platform as a service
Energy and cost-efficient solution giving you the best value and performance
Run the fine-tuned model on device or behind a firewall
What we offer
Uptime guarantee (99.5%)
Pipeline to process, chunk and vectorize documents to extract information accurately
Cost-effective solution to tailor your needs
Training and fine-tune of your models
Setting up on-prem or private cloud
Support and on-going improvements and updates
Faq
01 What is an SLM?
01 What is an SLM?
A machine learning model that's based on a large language model (LLM), but is smaller and less complex. SLMs can be used for a variety of tasks, such as sentiment analysis, content generation, and data retrieva
02 How much does it cost?
02 How much does it cost?
The free platform will let you upload one document sizing up-to 5MB. By default when you create an account, you will free 100 token that can be upgraded based on number of files and projects
03 How do you train models?
03 How do you train models?
You can use the command-line-interface to train a model that uses our powerful A-series GPUs to train / fine-tune LoRA adapters. Once trained, you can download the model locally using the command-line-interface or tool of your choice to run it on your local machine or deploy to your on-prem / cloud
04What is your base model?
04What is your base model?
We use Llama / Phi as our base model which is generally around 1B/3B in parameters based on the use-case and complexity
Use the power of Large Language Model in a small footprint , coverting your static data into Agents to streamline your existing process and be more productive without compromising your privacy within your budget