Appen Features
Data Governance (3)
User Access Management
Allows administrators to assign role-based user access for specific data sets
Dynamic Data Masking
Hides and masks sensitive data automatically based on user permissions
Data Lineage
Provides historical insights into original data sources and transformations made to data sets
Data Preparation (4)
Search
Offers simple search capabilities to discover specific data sets
Data Quality and Cleansing
Allows users and administrators to easily clean data to maintain quality and integrity
Data Transformation
Converts data formats of source data into the format required for the reporting system without mistakes
Data Modeling
Tools to (re)structure data in a manner that allows extracting insights quickly and accurately
Collaboration (4)
Commenting
Allows users to comment on data sets to help future users better interact and interpret the data
Profiling and Classification
Permits profiling of data sets for increased organization, both by users and machine learning
Business and Data Glossary
Creates a business glossary for faster understanding by the average business user
Metadata Management
Indexes metadata descriptions for easier searching and enhanced insights
Artificial Intelligence (3)
Machine Learning Recommendations
Automates recommendations for users based on machine learning functionality
Natural Language Query
Offers natural language querying functionality for non-technical users
Automatic Data Cleansing
Cleans data to improve quality via automation
Quality (4)
Labeler Quality
Gives user a metric to determine the quality of data labelers, based on consistency scores, domain knowledge, dynamic ground truth, and more.
Task Quality
Ensures that labeling tasks are accurate through consensus, review, anomaly detection, and more.
Data Quality
Ensures the data is of a high quality as compared to benchmark.
Human-in-the-Loop
Gives user the ability to review and edit labels.
Automation (2)
Machine Learning Pre-Labeling
Uses models to predict the correct label for a given input (image, video, audio, text, etc.).
Automatic Routing of Labeling
Automatically route input to the optimal labeler or labeling service based on predicted speed and cost.
Image Annotation (4)
Image Segmentation
Has the ability to place imaginary boxes or polygons around objects or pixels in an image.
Object Detection
has the ability to detect objects within images.
Object Tracking
Track unique object IDs across multiple video frames
Data Types
Supports a range of different types of images (satelite, thermal cameras, etc.)
Natural Language Annotation (3)
Named Entity Recognition
Gives user the ability to extract entities from text (such as locations and names).
Sentiment Detection
Gives user the ability to tag text based on its sentiment.
OCR
Gives user the ability to label and verify text data in an image.
Speech Annotation (2)
Transcription
Allows the user to transcribe audio.
Emotion Recognition
Gives user the ability to label emotions in recorded audio.
Generative AI (2)
AI Text Generation
Allows users to generate text based on a text prompt.
AI Text Summarization
Condenses long documents or text into a brief summary.
Agentic AI - Machine Learning Data Catalog (5)
Autonomous Task Execution
Capability to perform complex tasks without constant human input
Multi-step Planning
Ability to break down and plan multi-step processes
Cross-system Integration
Works across multiple software systems or databases
Adaptive Learning
Improves performance based on feedback and experience
Decision Making
Makes informed choices based on available data and objectives





