Start processing 100% of complex documents.
Submit your information to get started with super.AI Intelligent Document Processing (IDP).
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What’s the difference between super.AI IDP and UiPath Document Understanding? Let’s take a look at how the features of both platforms compare.
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Modern SaaS microservices
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Migrating to microservices
Leverages 5 different modern AI OCRs
Option to pick one of three OCRs
Latest AI/ML techniques
Rule-based, older AI/ML techniques
Multiple OCRs paired with multi-level AI delivers industry-leading results
Multiple extraction methods that must be configured manually
Includes sophisticated queues, routing, custom instructions, gamification, 150+ quality assessment mechanisms, and support for any data type
Includes sophisticated queues and routing; Lacks gamification, advanced quality measurement, ability to add instructions, and limited to documents
Deploy on-demand, curated human workers in your region for training, validation, and post-processing
Fuzzy matching against databases and ability to add any business logic in Python
Created separately using RPA bot
Users define quality, cost, and speed thresholds then super.AI guarantees the results
Simple AI confidence levels only
Multiple OCRs paired with multi-level AI delivers industry-leading results
Works well with structured docs
Multiple OCRs paired with multi-level AI delivers industry-leading results
Requires extensive setup, training, and tuning
Multiple OCRs paired with multi-level AI delivers industry-leading results
Requires extensive setup, training, and tuning
Leverages the best AI/ML model for each use case (e.g., KYC, redaction, damage detection, image classification, etc.)
Requires extensive setup, training, and tuning
Leverages the best AI/ML model for each use case (e.g., drone footage processing, license plate extraction, damage detection, redaction, etc.)
Requires extensive setup, training, and tuning
Leverages the best AI/ML model for each use case (e.g., transcription, speaker identification, etc.)
Requires extensive setup, training, and tuning
Leverages the best AI/ML model for each use case (e.g., classification, sentiment analysis, data extraction, etc.)
Requires extensive setup, training, and tuning
