Elotl

6/10Traction

Elotl provides a serverless infrastructure platform designed for deploying and managing microservices, specifically tailored for AI applications. The platform enables organizations to self-host large language models, retrieval-augmented generation, and vector databases, mitigating the high costs and data privacy risks associated with public GenAI inference APIs.

San Francisco, United States · HQ

Founded 201612200+ followers

Artificial Intelligence
Developer Tools
Software Only

Updated 22 months ago

Funding

Raised to date

$7.5MRaised 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.

Cisco InvestmentsNo round attributed

ciscoinvestments.com (opens in a new tab)investor website

HearstlabNo round attributed

hearstlab.com (opens in a new tab)investor website

Vertex Ventures USNo round attributed

Source unavailable

XYZ Venture CapitalNo round attributed

xyz.vc (opens in a new tab)investor website

Funding rounds are not available yet.

Founders

1 founder

Lisa Burton

Founder

Product

Problem

Organizations face challenges in deploying and managing AI applications due to the high costs, rate limits, and data privacy risks associated with public GenAI inference APIs. Self-hosting large language models, retrieval-augmented generation, and vector databases requires specialized infrastructure and expertise.

Solution

Elotl provides a GenAI infrastructure engine that enables organizations to self-host their AI workloads on public cloud in a secure, simple, cost-effective, and cloud-agnostic manner. The platform is built for AI and specialized for GPUs, ensuring AI initiatives can leverage cutting-edge breakthroughs. Elotl's Nodeless Kubernetes allows users to run applications without managing servers or clusters. The platform supports any LLM, RAG, VectorDB, and ML Framework.

Target Audience

The primary target audience includes organizations seeking to self-host AI applications to mitigate the costs and risks associated with public GenAI inference APIs.

Features

Serverless infrastructure for deploying and managing microservices, tailored for AI applications
Support for self-hosting large language models (LLMs), retrieval-augmented generation (RAG), and vector databases
Nodeless Kubernetes to run applications without managing servers or clusters
Luna Smart Autoscaling for public cloud Kubernetes clusters using on-demand and spot GPUs
Compatibility with any LLM, RAG, VectorDB, and ML Framework
Integration with SUSE AI