Ray Serve
NewScalable model serving library for building online inference APIs
Data collected ·ChatGPT, Perplexity, Google AI Mode·coverage 100%·next run
- Ray Serve ranks #61 of 61 in MLOps Platforms with an AI visibility score of 0 (SlateIndex, Nov 2, 2026).
- Ray Serve is most visible on ChatGPT (0) and least on Perplexity (0).
- AI engines name Ray Serve in 0 of the 30 MLOps Platforms buyer prompts SlateIndex tracks.
About
Company details for Ray Serve
Ray Serve is an open-source Python library for building scalable online inference APIs for machine learning models, including LLMs. It supports model composition, model multiplexing, built-in autoscaling, response streaming and dynamic request batching, and works with frameworks such as PyTorch and TensorFlow. It can run on a laptop, in a Docker container, on a managed Ray cluster or on Kubernetes via KubeRay. It is part of the open-source Ray project built by Anyscale. It ranks #61 of 61 in MLOps Platforms on SlateIndex and has a visibility score of 0 in the latest weekly run.
Its differentiator: independent scaling and fractional resources for each deployed model, with support for any ML model.
- Website
- ray.io
- Categories
- MLOps Platforms
- Headquarters
- San Francisco, California
- Company type
- Division of Anyscale
- Funding
- Series C
- Deployment
- Self-managed on a laptop, in a Docker container, on a managed Ray cluster, or on Kubernetes via KubeRay
- Compliance
- SOC 2 Type II, ISO/IEC 27001
- Support
- Ray Community Slack, Hands-on training and expert support from the Anyscale team that created Ray
Read from crunchbase.com, github.com, ray.io, gocodeo.com, trust.anyscale.com, anyscale.com · refreshed Nov 2, 2026.
AI visibility
Latest weekly run · Nov 2 · next run Nov 9
Visibility score trend
Weekly runs over the last 60 days, with up to 7 competitors. Click a name to hide or show its line.
Changes appear after the second weekly run in MLOps Platforms. MLflow leads the category at 50.9%.
Media
Website and product screenshots for Ray Serve
AI mentions & citations
Recent answers that name Ray Serve
No mentions in the latest run.
Products & features
What Ray Serve sells
Ray Serve
Scalable model serving library for building online inference APIs, with model composition, multiplexing, autoscaling and LLM serving features.
Target market & buyers
Developers and AI/ML engineering teams building Python-based AI applications
Notable customers include Canva, Instacart, Samsara, Ant Group.
Funding & recent developments
Funding
| Round | Year | Amount |
|---|---|---|
| Series A | 2019 | $20M |
| Series B | 2020 | $40M |
| Series C | 2021 | $100M |
| Series C | 2022 | $99M |
| Latest known round | Total raised |
|---|---|
| Series C | — |
Recent developments
- Jul 2026CompanyNscale agreed to acquire Anyscale
Reported at about $1.65 billion, a price cited from an anonymous source per Bloomberg. Nscale said Anyscale will keep its own branding and continue serving existing customers. The deal is expected to close in the second half of 2026, subject to regulatory approval.
- Jun 2026ProductPlatform skills for diagnosing Ray workloads through coding agents
Anyscale published platform skills that let coding agents diagnose Ray workloads.
- Jan 2026ProductAnyscale January 2026 platform release notes
Release notes cover CLI, operator for Kubernetes, and console updates.
- Sep 2025SecurityISO/IEC 27001 certification achieved
Anyscale achieved ISO/IEC 27001 certification with an A-LIGN audit.
- Jun 2025SecuritySOC 2 Type II audit completed
Anyscale announced its SOC 2 Type II audit completed with no testing exceptions.
Cite as: SlateIndex, “Ray Serve AI visibility profile”, https://slateindex.ai/brand/ray-serve, data of Nov 2, 2026. Licence: CC BY 4.0.