Anyscale

Anyscale

Platform for scaling AI workloads

About Anyscale

Simplify's Rating
Why Anyscale is rated
A
Rated A on Competitive Edge
Rated A on Growth Potential
Rated A on Rating Differentiation

Industries

Enterprise Software

AI & Machine Learning

Company Size

501-1,000

Company Stage

Series C

Total Funding

$252.5M

Headquarters

San Francisco, California

Founded

2019

Overview

Anyscale provides a platform designed to scale and productionize artificial intelligence (AI) and machine learning (ML) workloads. Its main product, Ray, is an open-source framework that helps users efficiently scale their AI applications across various fields, including Generative AI, Large Language Models (LLMs), and computer vision. Companies like OpenAI and Ant Group utilize Ray to train large models and enhance the performance and reliability of their ML systems. Anyscale's platform significantly improves scalability, latency, and cost-efficiency, with some clients experiencing over 90% enhancements in these areas. The company operates on a software-as-a-service (SaaS) model, allowing clients to subscribe to access Ray and its features, ensuring a consistent revenue stream. Anyscale's goal is to empower organizations to optimize their AI workloads and improve operational efficiency.

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Simplify's Take

What believers are saying

  • Anyscale's $100M Series C funding indicates strong investor confidence and growth potential.
  • Partnership with Nvidia enhances performance and cost-efficiency for AI deployments.
  • Anyscale Endpoints offers 10X cost-efficiency for popular open-source LLMs.

What critics are saying

  • ShadowRay vulnerability in Ray framework poses significant security risk with no patch.
  • OctoML's OctoAI service increases competition in AI infrastructure market.
  • Dependency on Nvidia's technology could be risky if Nvidia faces issues.

What makes Anyscale unique

  • Anyscale's Ray framework scales AI applications from laptops to cloud seamlessly.
  • Ray is widely used in Generative AI, LLMs, and computer vision fields.
  • Anyscale's SaaS model provides recurring revenue through subscription fees for Ray platform.

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Funding

Total Funding

$252.5M

Above

Industry Average

Funded Over

3 Rounds

Series C funding is usually for startups that are doing well and are looking for more money to fuel major growth, such as acquiring other companies, expanding into global markets, or launching new product lines. Investors typically include larger venture capital firms and private equity.
Series C Funding Comparison
Above Average

Industry standards

$50M
$50M
Medium
$62M
SeatGeek
$99M
Anyscale
$100M
Oura

Benefits

Medical, Dental, and Vision insurance

401K retirement savings

Flexible time off

FSA and Commuter benefits

Parental and family leave

Office & phone plan reimbursement

Growth & Insights and Company News

Headcount

6 month growth

8%

1 year growth

0%

2 year growth

-13%
Blockchain News
Oct 29th, 2024
Anyscale and Astronomer Collaborate to Enhance Scalable Machine Learning

This partnership allows organizations to effectively manage and scale their ML workflows by integrating Astronomer's workflow management capabilities with Anyscale's distributed computing power.

Datanami
Oct 1st, 2024
Anyscale Unveils New Products and AI Platform Enhancements at Ray Summit 2024

Anyscale unveils new products and AI Platform enhancements at Ray Summit 2024.

Financial Post
Jul 31st, 2024
Anyscale Names Industry Veteran Keerti Melkote Chief Executive Officer

SAN FRANCISCO, July 31, 2024 (GLOBE NEWSWIRE) - Anyscale, the company behind Ray, the open source framework for scalable AI, named industry veteran Keerti Melkote as chief executive officer following a year of 4x revenue growth and explosive open source adoption.

Blockchain News
Jun 6th, 2024
Anyscale and deepsense.ai Collaborate on Cross-Modal Search for E-commerce

Anyscale and deepsense.ai develop a scalable cross-modal image retrieval system for e-commerce.

VentureBeat
Mar 27th, 2024
‘Shadowray’ Vulnerability On Ray Framework Exposes Thousands Of Ai Workloads, Compute Power And Data

Join us in Atlanta on April 10th and explore the landscape of security workforce. We will explore the vision, benefits, and use cases of AI for security teams. Request an invite here. Thousands of companies use the Ray framework to scale and run highly complex, compute-intensive AI workloads — in fact, you’d be hard-pressed to find a large language model (LLM) that hasn’t been built on Ray. Those workloads contain loads of sensitive data, which, researchers have found, could be highly exposed through a critical vulnerability (CVE) in the open-source unified compute framework. For the last seven months, this flaw has allowed attackers to exploit thousands of companies’ AI production workloads, computing power, credentials, passwords, keys, tokens and “a trove” of other sensitive information, according to new research from Oligo Security. The vulnerability is under dispute — meaning that it is not considered a risk and has no patch. This makes it a “shadow vulnerability,” or one that doesn’t appear in scans. Fittingly, researchers have dubbed it “ShadowRay.”

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