Meryem Arik
CEO
TitanML
TitanML provides an enterprise-grade LLM cluster for high-performance language model inference, enabling organizations to deploy AI applications securely within their own infrastructure. This solution addresses the need for data privacy and control while optimizing operational costs and performance through advanced inference techniques.
- Artificial Intelligence
- Developer Tools
- Enterprise Software
- Software Only
Updated 7 months ago
Funding
Raised to date
$14.9MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
Organizations face challenges in deploying large language models (LLMs) securely and efficiently within their own infrastructure due to concerns about data privacy, control, and the high costs associated with inference. Relying on cloud-based APIs can expose sensitive data and limit customization options.
Solution
TitanML provides an enterprise-grade LLM cluster designed for high-performance language model inference, enabling organizations to deploy AI applications securely within their own environment. The TitanML Enterprise Stack offers a persistent API for state-of-the-art models, deployed on-premises, in a VPC, or on a public cloud, providing an alternative to cloud-based APIs. This solution allows organizations to maintain full control over their data and models while optimizing for specific security and performance requirements. By leveraging advanced inference techniques, TitanML enhances model performance and systematically improves the speed, quality, and cost-efficiency of AI deployments.
Target Audience
The primary target audience includes enterprises seeking to deploy and manage LLMs securely and efficiently within their own infrastructure, including those in regulated industries with strict data privacy requirements.
Features
- Flexible deployment options: on-premises, in VPC, or on a public cloud.
- Compatibility with OpenAI APIs for easy testing and migration of existing AI applications.
- Access to over 20,000 pre-trained models, including Llama and Mixtral, covering chat, multimodal, embeddings, rerank, and code.
- Advanced inference techniques to enhance model performance and optimize speed, quality, and cost-efficiency.
- GPU orchestration for efficient management and scaling of GPU resources.
- Enterprise-grade security measures and adherence to data privacy practices.