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Description
LabelFort, a comprehensive data annotation solution from Predusk AI, is designed specifically for AI teams that require their training data to meet rigorous audit standards. The platform utilizes AI pre-labeling to automate repetitive tasks, while one of five quality assurance workflows—ranging from single pass to double-blind reviews—ensures that every entry is ultimately validated by a human. Each dataset culminates in a detailed evidence pack that includes versioned pre-labels, a secure log documenting the labelling, review, and approval processes, along with inter-annotator agreement metrics, all aligned with compliance requirements such as the EU AI Act, HIPAA, GDPR, SOC 2, and DPDP documentation. Users can annotate a variety of data types—including images, videos, text, audio, LiDAR, DICOM, documents, and RLHF—through a unified platform equipped with an annotation canvas, ontology and form builder, QA console, audit log viewer, model registry, and dataset management features. With eight distinct user roles that incorporate unique routing and access protocols, teams have the flexibility to manage the platform independently or enhance their capabilities by engaging a trained domain specialist team via the Hire a Team service. This seamless integration of AI and human oversight ensures that data integrity is maintained throughout the annotation process, aiding in compliance and quality assurance.
Description
The Manna Manuscript Management System (MMS) is an advanced AI-driven platform that efficiently manages every stage of the manuscript process, from the initial submission and peer review all the way to publication. Tailored for use by academic publishers, journals, and conferences, it consolidates all editorial tasks, reviewer coordination, and tools for maintaining research integrity within a single, secure interface.
MMS is equipped with customizable workflows, options for blind and double-blind peer review, adaptive assessment forms, automated alerts, and access control based on user roles. Editors are empowered to allocate reviewers, oversee revisions, make decisions, and track progress using comprehensive real-time dashboards.
In addition, the platform features tools for detecting AI-generated content, performing plagiarism checks with adjustable thresholds, validating citations and references, integrating DOIs, converting to JATS XML, exporting metadata, and providing in-depth analytics for monitoring performance, ensuring a thorough approach to manuscript management that enhances productivity and quality in academic publishing. This comprehensive suite of features is designed to optimize the entire editorial process, making it a vital resource for scholarly communication.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Screenshots View All
No images available
Integrations
No details available.
Integrations
No details available.
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
$19
Free Trial
Yes
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
Yes
iPad App
Yes
Android App
Yes
Windows
Yes
Mac
Yes
Linux
Yes
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
No
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Predusk Technology Private Limited
Founded
2014
Country
India
Website
labelfort.ai/
Vendor Details
Company Name
Manna Analytics Private Limited
Founded
2025
Country
India
Website
mannasoftware.com
Product Features
Data Labeling
Human-in-the-loop
No
Labeling Automation
No
Labeling Quality
No
Performance Tracking
No
Polygon, Rectangle, Line, Point
No
SDK
No
Supports Audio Files
No
Task Management
No
Team Collaboration
No
Training Data Management
No
