Keyshape

Keyshape

Keyshape is a digital intelligence platform that allows users to easily extract key information from text and documents. It utilizes AI and machine learning to identify key concepts, entities, relationships and themes within content.
Keyshape image
information-extraction text-summarization semantic-search knowledge-graph

Keyshape: Digital Intelligence Platform

Extract key information from text and documents with AI-powered digital intelligence platform Keyshape, identifying key concepts, entities, relationships, and themes within content.

What is Keyshape?

Keyshape is a software tool designed to help users quickly analyze text and documents to identify the most important and relevant information. It utilizes natural language processing and machine learning algorithms to read content and automatically pull out key details.

Some of the main features of Keyshape include:

  • Entity, concept and relationship extraction - Identifies people, organizations, locations, dates, products, etc. mentioned in the text and understands connections between them.
  • Automatic summarization - Creates summaries by extracting the most salient sentences and key points.
  • Theme analysis - Detects the main subjects and topics covered in the content.
  • Custom model training - Allows users to further tailor the tool by training it on company-specific data.

Keyshape aims to save time and effort when reviewing large volumes of text content. It helps spotlight what matters most, so users can focus on the information that is most relevant to them. This makes it useful for market research, competitive intelligence, legal discovery and more.

The platform has an intuitive web interface that allows for upload of Word, PDF and text documents. It also offers integrations with various business apps to streamline workflows. Overall, Keyshape strives to make text analysis and information discovery quick, easy and effective using the power of AI.

Keyshape Features

Features

  1. Extracts key information from text and documents
  2. Utilizes AI and machine learning for text analysis
  3. Identifies key concepts, entities, relationships and themes
  4. Summarizes documents and highlights most relevant content
  5. Analyzes tone and sentiment of text
  6. Integrates with apps like Slack, Salesforce and Gmail

Pricing

  • Freemium
  • Subscription-Based

Pros

Saves time by automating text analysis

Provides insights quickly from large volumes of content

Easy to use with no coding required

Helps focus on most important information

Improves productivity and efficiency

Cons

May not understand highly technical or complex text

Limited customization compared to developing own NLP models

Accuracy depends on quality of training data

May require integration work to connect with other apps

AI bias issues if not trained properly


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