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Toolbit.ai
MLOpsAI Training DataData Labeling Platform

Labellerr

Automate AI training data preparation with smart quality assurance

Monthly Visits: 114.7K
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Labellerr

What is Labellerr?

Labellerr helps AI teams create high-quality labeled datasets for machine learning models. It combines automated annotation with human oversight to process millions of data points quickly. The platform supports images, videos, text, and audio while maintaining enterprise-grade security. Teams can reduce data preparation time by 90% and cut development costs by 80% through its smart QA system and MLOps integrations.

Key Features of Labellerr

  1. 1

    Automated Labeling

    AI-assisted annotation with human validation for rapid processing

  2. 2

    Smart QA

    Pre-trained models ensure 99.5% label accuracy automatically

  3. 3

    Multi-format Support

    Handles images, videos, PDFs, text, and audio in one platform

  4. 4

    MLOps Integration

    Direct push to AWS SageMaker, GCP Vertex AI, and custom environments

  5. 5

    Advanced Analytics

    Real-time project tracking and quality control dashboards

Labellerr AI Tool Use Cases

  • 📸
    Prepare computer vision datasets for autonomous vehicles
  • 📝
    Annotate NLP training data for chatbots
  • 🔍
    Create LLM training data from documents
  • ⚙️
    Manage enterprise-scale labeling projects

FAQs from Labellerr

What data formats does Labellerr support?

Supports CSV, JSON, COCO, Pascal VOC, and custom formats for export

How does Labellerr ensure data security?

Uses AES-256 encryption, TLS 1.2+ protocols, and offers private cloud hosting options

Can I use Labellerr for video annotation?

Yes, processes both images and video datasets with frame-by-frame labeling

Pros & Cons of Labellerr

Pros (4)

  • Processes millions of images/videos in weeks
  • 99.5% accuracy guarantee on labels
  • Enterprise-grade security with AES-256 encryption
  • Seamless integration with major cloud platforms

Cons (2)

  • No permanent free tier beyond 14-day trial
  • Primarily designed for enterprise teams (may be complex for individuals)

More Info About Labellerr

Who is using labellerr?

This tool is best for:

  1. AI development teams
  2. Computer vision engineers
  3. NLP developers
  4. Enterprise ML ops teams

Labellerr's Tags

Explore more niche AI tool websites by clicking on a tag* (works only if it has enough tools).

#AIModelDeployment #AIDataLabeling#ComputerVision#TrainingData

Integrate Labellerr With These Apps

Labellerr can be integrated with these apps and services:

  • AWS
  • GCP
  • Azure
  • AWS SageMaker
  • GCP Vertex AI

Website Analytics of Labellerr

Labellerr Website Traffic & SEO Analysis:

Recent data shows that Labellerr has 114.7K monthly visits (36.6% increase from the previous month), 48.0% bounce rate, and average 1.73 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by India contributing 14% of total traffic. SEO performance is shown by 5 tracked keywords, with "labellerr" being the top-performing keyword with 380 monthly searches. See below for more info.

Monthly Visits

114.7K

(+36.6%)

Pages per Visit

1.73

Bounce Rate

48.0%

Average Time on Site

33s

Traffic Trend(May 2025 - Jul 2025)

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Top Keywords

SEO KeywordVolumeCPC
labellerr
380$4.09
end to end machine learning pipeline
270-
is openai operator like rpa
260-
dpo vs ppo
790-
vision language action models
1.2K-

Traffic Sources Distribution

Traffic Share by Source

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Source Breakdown Details

SourceTraffic Share
Direct
32%
Search
56%
Social
3%
Referrals
8%
Paid Referrals
1%

Global Traffic Distribution

Traffic Share by Country

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Geographic Breakdown Details of top 5 countries

Country NameTraffic Share
India14%
United States13%
Vietnam5%
Germany4%
United Kingdom3%
Analytics data is estimated (from third-party analytics providers) and for reference only.

🚀 Labellerr Launch Badge

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How to use: Simply copy and paste the embed code into your homepage or footer HTML to display it instantly and build community support.

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