Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
KServe is a robust model inference platform on Kubernetes that emphasizes high scalability and adherence to standards, making it ideal for trusted AI applications. This platform is tailored for scenarios requiring significant scalability and delivers a consistent and efficient inference protocol compatible with various machine learning frameworks. It supports contemporary serverless inference workloads, equipped with autoscaling features that can even scale to zero when utilizing GPU resources. Through the innovative ModelMesh architecture, KServe ensures exceptional scalability, optimized density packing, and smart routing capabilities. Moreover, it offers straightforward and modular deployment options for machine learning in production, encompassing prediction, pre/post-processing, monitoring, and explainability. Advanced deployment strategies, including canary rollouts, experimentation, ensembles, and transformers, can also be implemented. ModelMesh plays a crucial role by dynamically managing the loading and unloading of AI models in memory, achieving a balance between user responsiveness and the computational demands placed on resources. This flexibility allows organizations to adapt their ML serving strategies to meet changing needs efficiently.
Description
A comprehensive platform for managing projects, models, and hosting, designed for organizations to transform their data and algorithms into cohesive, execution-ready AI strategies. Effortlessly build, train, and oversee models while ensuring security throughout the process. Create AI-driven products that can be accessed at any time and from any location. This approach minimizes the risks associated with AI investments and enhances strategic adaptability. It features fully automated processes for model testing, evaluation, deployment, scaling, and hardware load balancing, catering to both real-time low-latency high-throughput inference and longer batch inference. The pricing structure operates on a pay-per-second-of-use basis, including a service-level agreement (SLA) and comprehensive governance, monitoring, and auditing features. The platform boasts an intuitive interface that serves as a centralized hub for project management, dataset creation, visualization, and model training, all facilitated through collaborative and reproducible workflows. This empowers teams to work together seamlessly, ensuring that the development of AI solutions is efficient and effective.
API Access
Has API
Yes
API Access
Has API
No
Integrations
Amazon Web Services (AWS)
No
Bloomberg
Yes
Docker
Yes
Gojek
Yes
Google Cloud Platform
No
IBM Cloud
Yes
Kubeflow
Yes
Kubernetes
Yes
Microsoft Azure
No
NAVER
Yes
Integrations
Amazon Web Services (AWS)
Yes
Bloomberg
No
Docker
No
Gojek
No
Google Cloud Platform
Yes
IBM Cloud
No
Kubeflow
No
Kubernetes
No
Microsoft Azure
Yes
NAVER
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
Yes
Mac
Yes
Linux
Yes
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
KServe
Website
kserve.github.io/website/latest/
Vendor Details
Company Name
SquareFactory
Founded
2022
Country
Switzerland
Website
www.squarefactory.io/product/
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No
Product Features
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No