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ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

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Average Ratings 0 Ratings

Total 0 out of 5 stars
ease 0 out of 5 stars
features 0 out of 5 stars
design 0 out of 5 stars
support 0 out of 5 stars

No User Reviews. Be the first to provide a review:

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Description

Klique is an enterprise AI infrastructure management platform designed to help organizations deploy, govern, and optimize artificial intelligence workloads across multiple environments. The software provides a unified control plane for managing large language models, autonomous AI agents, GPU resources, and machine learning applications. Its intelligent routing engine automatically directs requests to suitable models based on organizational policies, performance requirements, response latency, and operating costs. Klique supports internally hosted models, open-source models, and external AI services from providers such as OpenAI and Anthropic. Its governance engine provides centralized authentication, role-based access controls, token budgets, usage quotas, audit trails, and detailed cost attribution. GPU orchestration capabilities enable resource pooling, workload prioritization, fractional GPU allocation, and automated scheduling across Kubernetes clusters and cloud infrastructure. The platform also provides managed development environments, model deployment tools, experiment tracking, and reusable workflows for AI development teams. Integrations with Claude Code, Codex, ChatGPT, and other agentic applications allow organizations to provide governed access to AI tools and computing resources. Klique supports on-premises, public cloud, hybrid, and air-gapped deployments, enabling enterprises to manage AI infrastructure while maintaining centralized security policies and operational visibility.

Description

MLflow is an open-source suite designed to oversee the machine learning lifecycle, encompassing aspects such as experimentation, reproducibility, deployment, and a centralized model registry. The platform features four main components that facilitate various tasks: tracking and querying experiments encompassing code, data, configurations, and outcomes; packaging data science code to ensure reproducibility across multiple platforms; deploying machine learning models across various serving environments; and storing, annotating, discovering, and managing models in a unified repository. Among these, the MLflow Tracking component provides both an API and a user interface for logging essential aspects like parameters, code versions, metrics, and output files generated during the execution of machine learning tasks, enabling later visualization of results. It allows for logging and querying experiments through several interfaces, including Python, REST, R API, and Java API. Furthermore, an MLflow Project is a structured format for organizing data science code, ensuring it can be reused and reproduced easily, with a focus on established conventions. Additionally, the Projects component comes equipped with an API and command-line tools specifically designed for executing these projects effectively. Overall, MLflow streamlines the management of machine learning workflows, making it easier for teams to collaborate and iterate on their models.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Apache Spark No 
Apolo No 
Axolotl No 
Azure Data Science Virtual Machines No 
Azure Machine Learning No 
Cranium No 
Docker No 
Google Cloud Platform No 
Kedro No 
Kubernetes No 
LLaMA-Factory No 
Microsoft 365 No 
OpenMetadata No 
Ragas No 
Ray No 
Superwise No 
UbiOps No 
Unity Catalog No 
Vectice No 
ZenML No 

Integrations

Apache Spark Yes 
Apolo Yes 
Axolotl Yes 
Azure Data Science Virtual Machines Yes 
Azure Machine Learning Yes 
Cranium Yes 
Docker Yes 
Google Cloud Platform Yes 
Kedro Yes 
Kubernetes Yes 
LLaMA-Factory Yes 
Microsoft 365 Yes 
OpenMetadata Yes 
Ragas Yes 
Ray Yes 
Superwise Yes 
UbiOps Yes 
Unity Catalog Yes 
Vectice Yes 
ZenML Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version 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 

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 Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

Klique

Founded

2022

Country

United States

Website

klique.ai/

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

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 

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