Average Ratings 0 Ratings

Total
ease
features
design
support

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

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

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

Write a Review

Description

You can import findings from more than 20 popular security and pentesting tools and present them in a variety of formats, including Word, Excel and HTML. Multiple methodologies can be used for different stages of a project. This will allow you to keep track of all your tasks, and ensure consistent results throughout your organization. It is easier to work together when security project data, tool outputs and scope, results, screenshots, and notes are all centralized. To keep everyone on the same page, track changes, give feedback and push out updated findings, you can track them all. You don't need to learn new technologies. Simply combine the outputs from your favorite security tools, such as Nessues and Burp, Nmap, and more to create custom reports. Our simple, yet powerful templates will help you create reports in a matter of minutes, not days. Dradis Gateway can help you overcome the limitations of static security reports. You can share the results of security assessments in real time.

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

Cisco Duo Yes 
Comet LLM No 
Databricks No 
Determined AI No 
Docker No 
Flyte No 
Invicti Yes 
Jozu No 
Microsoft 365 No 
Microsoft Azure Yes 
OWASP ZAP Yes 
Okta Yes 
OpenMetadata No 
Ragas No 
ServiceNow Yes 
VMware Cloud Yes 
VirtualBox Yes 
ZenML No 
neptune.ai No 

Integrations

Cisco Duo No 
Comet LLM Yes 
Databricks Yes 
Determined AI Yes 
Docker Yes 
Flyte Yes 
Invicti No 
Jozu Yes 
Microsoft 365 Yes 
Microsoft Azure No 
OWASP ZAP No 
Okta No 
OpenMetadata Yes 
Ragas Yes 
ServiceNow No 
VMware Cloud No 
VirtualBox No 
ZenML Yes 
neptune.ai Yes 

Pricing Details

$79 per month
Per user per month
billed annually
Free Trial No 
Free Version Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based No 
On-Premises Yes 
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) Yes 
In Person No 

Types of Training

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

Vendor Details

Company Name

Dradis Framework

Founded

2010

Country

United Kingdom

Website

dradis.com

Vendor Details

Company Name

MLflow

Founded

2018

Country

United States

Website

mlflow.org

Product Features

Collaboration

Brainstorming No 
Calendar Management Yes 
Chat / Messaging Yes 
Contact Management Yes 
Content Management Yes 
Document Management Yes 
Project Management Yes 
Real Time Editing Yes 
Task Management Yes 
Version Control Yes 
Video Conferencing 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 

Alternatives

Alternatives

Union Cloud Reviews

Union Cloud

Union.ai
Reporter Reviews

Reporter

Security Reporter