Machine Learning

Automatic document classification and data capture with advanced machine learning techniques that learn and improve over time.

Classify unstructured and semi-structured content

KnowledgeLake has developed a new multifaceted approach to classifying unstructured and semi-structured content and extracting data from that content. This new approach leverages several recent innovations in machine learning and computer vision that enable the platform to solve unique content problems—all without customization and coding or expensive, lengthy projects.

Classify unstructured and semi-structured content

KnowledgeLake has developed a new multifaceted approach to classifying unstructured and semi-structured content and extracting data from that content. This new approach leverages several recent innovations in machine learning and computer vision that enable the platform to solve unique content problems—all without customization and coding or expensive, lengthy projects.

What is machine learning?

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience with content, without being explicitly programmed. The primary aim is to allow systems to learn automatically without human intervention or assistance and adjust actions accordingly. Supervised machine-learning algorithms can apply what has been learned in the past to new data.

The unique KnowledgeLake approach to classifying content with this technology was first to create a proprietary neural network, training it on how to identify similar documents. An approach similar to facial recognition, but applied to content classification, reduces the need to manually tag metadata and eliminates traditionally laborious document preparation.

Once a document is identified, extracting relevant information is key. KnowledgeLake’s patent-pending approach enables its platform to convert this unstructured document to structured information without the need for full-page optical character recognition (OCR). The result is a system with significantly faster processing power and more resilience to image quality issues—all with greater accuracy than legacy capture solutions.

Combine all of this with a supervised learning capability and the traditional reliance on IT or developer-level resources to code complicated rule sets is removed. Instead, users are empowered to teach the system about new document types, improving the software through their daily use.

What is machine learning?

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience with content, without being explicitly programmed. The primary aim is to allow systems to learn automatically without human intervention or assistance and adjust actions accordingly. Supervised machine-learning algorithms can apply what has been learned in the past to new data.

The unique KnowledgeLake approach to classifying content with this technology was first to create a proprietary neural network, training it on how to identify similar documents. An approach similar to facial recognition, but applied to content classification, reduces the need to manually tag metadata and eliminates traditionally laborious document preparation.

Once a document is identified, extracting relevant information is key. KnowledgeLake’s patent-pending approach enables its platform to convert this unstructured document to structured information without the need for full-page optical character recognition (OCR). The result is a system with significantly faster processing power and more resilience to image quality issues—all with greater accuracy than legacy capture solutions.

Combine all of this with a supervised learning capability and the traditional reliance on IT or developer-level resources to code complicated rule sets is removed. Instead, users are empowered to teach the system about new document types, improving the software through their daily use.

ADVANTAGES

Regardless of how content comes into your organization, KnowledgeLake makes interacting with documents and data easier and more effective. 

Next-generation classification

Proprietary neural networks are used to automatically find like documents, identify what they are, and sort them under the correct classification.

Picture recognition for improved accuracy

Our machine learning-based recognition technology quickly captures information—even from skewed or lower-resolution images—eliminating the need to rely solely on unwieldy traditional recognition engines.

Gain performance improvements

Classification is completed more quickly than with traditional approaches, offering easy onboarding of new content types. Move quickly from manual processing to a highly optimized system.

ADVANTAGES

Regardless of how content comes into your organization, KnowledgeLake makes interacting with documents and data easier and more effective. 

Next-Generation Classification

Proprietary neural networks are used to automatically find like documents, identify what they are, and sort them under the correct classification.

Picture Recognition for Improved Accuracy

Our machine learning-based recognition technology quickly captures information—even from skewed or lower-resolution images—eliminating the need to rely solely on unwieldy traditional recognition engines.

Gain Performance Improvements

Classification is completed more quickly than with traditional approaches, offering easy onboarding of new content types. Move quickly from manual processing to a highly optimized system.

What could you do with the KnowledgeLake platform?

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