LabelFort

LabelFort

Predusk Technology Private Limited
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About

LabelFort is an audit-ready data annotation platform and managed annotation service from Predusk AI, built for AI teams whose training data has to survive an audit. AI pre-labelling handles the mechanical work, one of five QA workflows (single pass, maker checker, double-blind, AI review, AI consensus) reviews every record and ends in a human decision, and every dataset exports as an evidence pack: versioned pre-labels, an immutable log of who labelled, reviewed, and approved each record, and per-cohort inter-annotator agreement, mapped to EU AI Act, HIPAA, GDPR, SOC 2, and DPDP documentation. Image, video, text, audio, LiDAR, DICOM, document, and RLHF annotation run on one platform with an annotation canvas, ontology and form builder, QA console, audit log viewer, model registry, and dataset manager. Eight roles with separate routing and access checks. Teams can run the platform themselves or add a trained domain specialist team through Hire a Team.

About

People For AI is labeling your data. Using our service, you will obtain high-quality training data for your computer vision, NLP or speech recognition algorithms. We use AI-powered data labeling tools that are adapted to your task. With the right tool, the right team and our methodology, you data is in good hands. As we only hired long-term labelers, we specialized in high-value data annotation, however we can manage any kind of projects. Check our CSR report on our website to know more about our labelers!

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Not Supported
Linux Not Supported
Cloud Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Audience

AI and machine learning teams in healthcare and life sciences, autonomous vehicles and geospatial, public sector and defense, financial services, and robotics that must show a regulator or procurement reviewer who labelled what, under which guideline, and with what agreement score

Audience

AI Team Lead, CTOs, Data scientists, Computer vision Engineers, AI-first companies

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Not Supported

Screenshots and Videos

No images available

Screenshots and Videos

No images available

Pricing

No information available.
Free Version Not Supported
Free Trial Not Supported

Pricing

Free trials are available,
POC project (under 1000€) are availables.
Production project begin from 200 hours of labeling.
Free Version Not Supported
Free Trial Supported

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 5.0 / 5
ease 4.7 / 5
features 4.6 / 5
design 4.6 / 5
support 4.9 / 5

Pros & Cons from Real Users

Pros

  • - open to the understanding of the client's needs - provided high-quality service - delivery time was always within the expectation - open to further discussions and refinements
  • It is a real pleasure to work with PFAI: - They are always nice and swift in their responses. - It is super easy and quick to set up a new annotation project with them. - They deliver high quality.
  • The contact was really good. Quick, and arranged video calls with sole purpose to understand my needs precisely. Labeling project went swiftly and I had no doubts about the quality of data I received. I felt like they really cared to deliver best to my needs and no detail was omitted.
  • I have worked with People For AI on a complex computer vision project that required significant learning on unusual data with precise labeling. They quickly set up a labeling tool that was well-suited to our use case, which helped us efficiently incorporate the annotation tasks into our training pipeline. The labeling team asked many questions, showed a keen attention to detail, and considered edge cases thoroughly. They achieved impressive results after only a few days of training. It was also beneficial to have direct communication with the project manager in charge of production, allowing for immediate feedback and daily updates on progress. For the second labeling task, which occurred 18 months later, I was pleased to discover that the same team was once again involved in the project.
  • We really liked the ethics of the company, as well as their long-term approach to work and their people. They were fast to respond to our queries, and were able to get work done rapidly to meet the demand of our own customers. The people doing the labelling work were quick to respond to new feedback to improve the labelling being done. They were flexible to adapt to using our custom-designed tools. They provided us with detailed information about the labelling work being done.

Cons

  • I cannot se any cons in working with People For AI.
  • I cannot think of any cons in working with PFAI and have nothing to complain about.
  • Maybe teams english was difficult to understand sometimes, but I don't think that matters.
  • There is nothing that comes to my mind regarding the cons of using the data annotation services provided by People for AI.
  • Some sort of integrated web-based platform to see work in progress would be nice, but this did not prevent People for AI from sharing information with us by other means (e.g. shared spreadsheets).

Training

Documentation Not Supported
Webinars Not Supported
Live Online Supported
In Person Not Supported

Training

Documentation Not Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Company Information

Predusk Technology Private Limited
Founded: 2014
India
labelfort.ai/

Company Information

People For AI
Founded: 2020
France
peopleforai.com

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Categories

Data Annotation Supported
Data Labeling Supported

Categories

Data Annotation Supported
Data Labeling Supported

Data Labeling Features

Human-in-the-loop Supported
Labeling Automation Supported
Labeling Quality Supported
Performance Tracking Supported
Polygon, Rectangle, Line, Point Supported
SDK Not Supported
Supports Audio Files Not Supported
Task Management Not Supported
Team Collaboration Supported
Training Data Management Not Supported

Integrations

Kili Technology Not Supported
Labelbox Not Supported
SuperAnnotate Not Supported
V7 Darwin Not Supported

Integrations

Kili Technology Supported
Labelbox Supported
SuperAnnotate Supported
V7 Darwin Supported
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