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What is Mona?

Mona is a versatile and smart monitoring platform designed for artificial intelligence and machine learning applications. Data science teams utilize Mona’s robust analytical capabilities to obtain detailed insights into their data and model performance, allowing them to identify problems in specific data segments, thereby minimizing business risks and highlighting areas that require enhancement. With the ability to monitor custom metrics for any AI application across various industries, Mona seamlessly integrates with existing technology infrastructures. Since our inception in 2018, we have dedicated ourselves to enabling data teams to enhance the effectiveness and reliability of AI, while instilling greater confidence among business and technology leaders in their capacity to harness AI's potential effectively. Our goal has been to create a leading intelligent monitoring platform that offers continuous insights to support data and AI teams in mitigating risks, enhancing operational efficiency, and ultimately crafting more valuable AI solutions. Various enterprises across different sectors use Mona for applications in natural language processing, speech recognition, computer vision, and machine learning. Founded by seasoned product leaders hailing from Google and McKinsey & Co, and supported by prominent venture capitalists, Mona is headquartered in Atlanta, Georgia. In 2021, Mona earned recognition from Gartner as a Cool Vendor in the realm of AI operationalization and engineering, further solidifying its reputation in the industry. Our commitment to innovation and excellence continues to drive us forward in the rapidly evolving landscape of AI.

What is Evidently AI?

A comprehensive open-source platform designed for monitoring machine learning models provides extensive observability capabilities. This platform empowers users to assess, test, and manage models throughout their lifecycle, from validation to deployment. It is tailored to accommodate various data types, including tabular data, natural language processing, and large language models, appealing to both data scientists and ML engineers. With all essential tools for ensuring the dependable functioning of ML systems in production settings, it allows for an initial focus on simple ad hoc evaluations, which can later evolve into a full-scale monitoring setup. All features are seamlessly integrated within a single platform, boasting a unified API and consistent metrics. Usability, aesthetics, and easy sharing of insights are central priorities in its design. Users gain valuable insights into data quality and model performance, simplifying exploration and troubleshooting processes. Installation is quick, requiring just a minute, which facilitates immediate testing before deployment, validation in real-time environments, and checks with every model update. The platform also streamlines the setup process by automatically generating test scenarios derived from a reference dataset, relieving users of manual configuration burdens. It allows users to monitor every aspect of their data, models, and testing results. By proactively detecting and resolving issues with models in production, it guarantees sustained high performance and encourages continuous improvement. Furthermore, the tool's adaptability makes it ideal for teams of any scale, promoting collaborative efforts to uphold the quality of ML systems. This ensures that regardless of the team's size, they can efficiently manage and maintain their machine learning operations.

Media

Media

Integrations Supported

Amazon Web Services (AWS)
DataRobot
Google Chat
Microsoft Azure
Microsoft Teams
New Relic
PagerDuty
Slack
Snowflake
TensorFlow

Integrations Supported

ZenML

API Availability

API Availability

Pricing Information

Pricing not provided
Free Trial Offered?

Pricing Information

$500 per month
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

Mona

Date Founded

2018

Company Location

United States

Company Website

www.monalabs.io

Company Facts

Organization Name

Evidently AI

Date Founded

2020

Company Location

United States

Company Website

www.evidentlyai.com

Categories and Features

AI Observability

Not specified

Anomaly Detection

Not specified

Artificial Intelligence

For Healthcare
For Sales
For eCommerce
Machine Learning
Natural Language Processing
Predictive Analytics
Process/Workflow Automation

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics

Machine Learning

Deep Learning
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Visualization

Categories and Features

AI Development

Not specified

AI Observability

Not specified

Data Quality

Not specified

Machine Learning

Not specified

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