Create LLMs Tailored for Your Use Cases
Developing an LLM is complex—and cloud-hosted proprietary models are expensive, not specific to a use case, and do not secure your organization’s data.
Access Open-Source LLMs
Test a variety of customizable large-language models with various parameter counts, sizes, and accuracy levels.
Ensure Security
Keep data secure with on-premises deployment for unparalleled flexibility and control over your generative AI projects.
Learn from the Experts
Anaconda’s Professional Services team will assist with implementation to ensure outcomes meet your requirements.
Resources
Generative AI with IBM and Anaconda
Discover the power of Anaconda and IBM WatsonX for LLMs.
Anaconda Professional Services
Get help building and implementing generative AI from Anaconda Experts.
Data Preparation for Large Language Models
Learn how to transform and clean data for LLMs.
Transform Your Organization's AI Capabilities Today
FAQ
What is an on-premise LLM solution?
An on-premise LLM solution is a large language model deployed within your organization’s own infrastructure. A cloud-based LLM, on the other hand, operates on external infrastructure managed by a cloud service provider.
What are the benefits of an on-premise LLM?
An on-premise LLM provides enhanced data security and privacy, ensuring that sensitive information stays within your security boundaries. It offers better compliance control, reduced latency for faster performance, and the ability to customize the model for specific business needs. This makes it a strong choice for organizations in regulated or high-security industries.
What types of LLMs can be deployed on-premise?
On-premise deployment supports a range of LLMs, including open-source models like Llama 2 and Falcon, as well as proprietary models designed for enterprise use. These models can vary in size and capabilities, from general-purpose models to those fine-tuned for specific tasks like code generation, document summarization, or natural language understanding.
What infrastructure is required to deploy an LLM on-premise?
Deploying an LLM on-premise requires high-performance hardware like GPUs or TPUs for efficient processing, along with adequate storage for the model and associated data. You’ll also need tools for managing the deployment, such as containerization (e.g., Docker) or orchestration platforms (e.g., Kubernetes), to ensure scalability.
What factors affect the performance of an on-premise LLM?
The performance of an on-premise LLM depends on factors like the model size, the computational power of your hardware, and the efficiency of your software stack. Other considerations include storage speed and how well the model is optimized for your specific use case. To get the most out of an on-premise LLM, mastering prompt engineering — the art of crafting input prompts that elicit the most accurate responses — is essential, as it directly impacts the relevance and quality of the model’s outputs.
How scalable is Anaconda’s on-premise LLM solution?
Anaconda’s on-premise LLM solution is highly scalable, allowing you to adjust resources to meet your needs, whether you’re supporting small workloads or enterprise-level deployments. It’s designed to grow with your organization, ensuring reliable performance at any scale.
Is Anaconda’s on-premise LLM secure?
Yes, Anaconda’s on-premise LLM is built with security in mind, keeping all data within your infrastructure to minimize exposure. It also supports advanced security measures, such as encryption and role-based access control, to safeguard your sensitive information.
What data privacy regulations does Anaconda’s on-premise LLM comply with?
Anaconda’s on-premise LLM is designed to support compliance with key data privacy regulations such as GDPR, HIPAA, among other industry-specific standards. Its flexibility allows you to meet the requirements of any region or sector.
Can Anaconda’s on-premise LLM solution operate offline?
Yes, Anaconda’s on-premise LLM can operate fully offline, making it ideal for environments where internet connectivity is limited or where strict data isolation is required. With Anaconda AI Platform, you can bring the power of LLMs directly to your desktop — allowing for seamless, offline use of LLMs, in hand with enhanced security and the flexibility to scale based on your needs.
