Clear, Fast & Unlimited. Residential & Mobile Proxies For Best Price.
sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Which is more popular?
Based on our record, 17track
seems to be more popular. It has been mentioned
2 times
since March 2021.
social mentions
2 vs 0
Shipping and Tracking popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
Comprehensive Tracking 17track supports tracking for over 500 carriers worldwide, making it a versatile tool for monitoring packages from various shipping services.
User-Friendly Interface The platform features a clean and intuitive interface, allowing users to easily input tracking numbers and view the status of their shipments.
Real-Time Updates Users get real-time updates on the status and location of their packages, which helps in tracking the exact progress of deliveries.
Multi-Language Support 17track is available in multiple languages, making it accessible to a global audience.
Mobile App Availability The service offers mobile apps for both iOS and Android, enabling users to track packages on-the-go.
Possible disadvantages
Advertisements The free version of 17track includes advertisements, which may be distracting for users.
Data Privacy Concerns Users may be concerned about sharing their tracking numbers and personal data with a third-party platform.
Occasional Inaccuracies Some users report occasional inaccuracies in tracking information, which can lead to confusion about the actual status of their shipments.
Limited Advanced Features While great for basic tracking, 17track may lack some advanced features found in specialized logistics and supply chain management tools.
Dependency on Carrier Updates The accuracy and timeliness of tracking information depend on the data provided by the carriers, which can vary in quality.
Efficient Data Curation Lightly uses active learning and self-supervised learning techniques to help teams select the most valuable and diverse subset of data for labeling, reducing the amount of data needed for training while maintaining model performance.
Reduces Labeling Costs By intelligently selecting which images or videos to label, Lightly can significantly cut down on the manual annotation costs and time required for building computer vision datasets.
Self-Supervised Learning Integration The platform leverages self-supervised learning methods to extract meaningful embeddings from unlabeled data, enabling better understanding of dataset structure and redundancy before labeling.
Scalable for Large Datasets Lightly is designed to handle large-scale image and video datasets, making it suitable for enterprises dealing with massive amounts of visual data in computer vision projects.
Integration with ML Workflows Lightly offers APIs and integrations that allow it to fit into existing machine learning pipelines, working alongside popular annotation tools and cloud storage solutions.
Possible disadvantages
Learning Curve Teams new to active learning and self-supervised learning concepts may face a learning curve in understanding how to best utilize Lightly's data curation capabilities.
Narrow Use Case Focus Lightly is primarily focused on computer vision data curation, which may limit its usefulness for teams working with other data types such as text, audio, or tabular data.
Dependency on Data Quality The effectiveness of Lightly's curation algorithms depends heavily on the quality and representativeness of the initial dataset, which can limit results if the source data is poor.
Pricing for Smaller Teams Depending on the pricing tier, smaller teams or individual developers might find the cost of enterprise-level data curation features less accessible compared to open-source alternatives.
Requires Technical Expertise Effectively leveraging Lightly's advanced features like self-supervised learning models may require a certain level of machine learning expertise, which could be a barrier for less technical teams.
Analysis
An editorial look at what each product does well and who it suits.
17trackLightly
Overall verdict
Yes, 17track is considered to be a good and reliable tool for tracking packages from multiple carriers.
Why this product is good
17track is widely regarded as a good package tracking platform because it allows users to track shipments from a vast number of international and domestic carriers, making it convenient for those who shop online from different sources. The platform also offers a user-friendly interface, mobile app support, and detailed tracking information.
Recommended for
17track is recommended for individuals who frequently shop online from various international retailers and need a centralized tool to track parcels from numerous carriers in one place. It's also useful for small businesses that want to provide customers with an easy way to track their orders.
Overall verdict
Lightly is a solid, well-regarded platform for data curation and active learning in computer vision, offering strong tooling for selecting the most valuable images/frames to label, which helps teams reduce annotation costs and improve model performance efficiently.
Why this product is good
Focuses on smart data selection and curation, helping avoid wasted labeling budget on redundant data
Offers both open-source (Lightly SSL) and commercial (Lightly Worker/Platform) options for flexibility
Uses self-supervised learning techniques to find diverse, representative, or edge-case samples
Integrates with common MLOps and labeling tools, fitting into existing computer vision pipelines
Scales to large unlabeled datasets, making it useful for teams with massive raw data but limited labeling resources
Provides visualization and embedding tools to explore dataset distribution and detect biases or gaps
Recommended for
Computer vision teams looking to reduce labeling costs through smarter data selection
ML engineers building active learning pipelines
Companies with large volumes of unlabeled image or video data
Teams wanting to improve model performance by curating more diverse or representative training sets
Organizations needing to detect dataset bias, redundancy, or edge cases before annotation
OneTracker – Package Tracker is an app by OneTracker Team that helps users track all their delivery vehicles and staff to increase the productivity of their delivery business.
TrackChecker Mobile app features tracking of parcels and online orders, so users don’t have to worry about losing a package by tracking the parcel right on their mobile phone screen.
Compare TrackChecker Mobile to 17track or Lightly:
Package Tracker – Amazon, eBay, Royal Mail, Hermes app helps users in viewing all the necessary information about domestic and international parcels by scanning the barcode of the parcel using the phone’s camera.