Innovative High-quality Document Summarizer.

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Did you know that ...

  • 80% of business-relevant information are
    unstructured text (Gartner Group 2020)

  • «... and less than 1% of all unstructured data is
    even analyzed» (..., Prof. Thomas Davenport/ MIT)
How to increase value

Is there a better way to increase the value of sparsely used information than by creating easy-to-read summaries?


How to avoid information overload?


Have you ever tried it with high-quality, easy-to-read summaries?

Summaries can be helpful if they ...

  • characterize the true content, i.e. are not misleading

  • reflect the structure of the original document
    (presumably with subtitles per section)

  • are easy-to-read

  • allow a link to the position in the original document

Benefits of the Summarizer


Time and cost saving; particularly for long documents



Fast view on the whole; separate wheat from the chaff



Common basis of understanding within work groups



Direct links of the summary positions to the original document

... and with one click: 😉 Display the full text behind the current summary section

Based on the semantic AI tool InfoCodex, specialized in the analysis of unstructured data, an innovative document summarizer has been developed to produce high-quality summaries. These summaries have the following properties:

  • They reflect the true content because Infocodex with its comprehensive and universal linguistic knowledge repository understands the content without any training (unlike its competitors). They can immediately be applied in any topic.

  • Documents are automatically divided into plausible subsections entitled by subheadings by means AI supported methods.

  • The summaries reflect the structure of the original document as set by the author (see example below).

  • They are easy to read and they facilitate the communication withln workgroups.

  • Significant time savings: 5-15 minutes per day for typical users / 30-60 for professional readers (estimates of 7 test readers).

    Specific Applications (with long documents)
    • research papers

    • medical/legal expertises

    • contract management

    • legal regulations / ordinances

    • ligitations / court proceedings

    • customer histories etc.

    Example of a generated summary

    Example of a summary (divided into plausible subsections) for

    What is Big Data Analytics and Why is it Important? (Summary)

    Organizations can use big data analytics systems and software to make data-driven decisions that can improve business-related outcomes. ... Data analysts, data scientists , predictive modelers, statisticians and other analytics professionals collect, process, clean and analyze growing volumes of structured transaction data as well as other forms of data not used by conventional BI and analytics programs. ... Data professionals scrub the data using scripting tools or data quality software.
    software | big data | tool | business | data warehouse | mining | data file

    Key big data analytics technologies and ...

    Organizations use predictive analytics tools for fraud detection, marketing, risk assessment and operations. ... Data preprocessing software, which prepares data for further analysis. ... Big data has become increasingly beneficial in supply chain analytics. ... Also, big supply chain analytics implements highly effective statistical methods on new and existing data sources.
    software | tool | technology | cloud | enterprise resource planning | analysis | data warehouse

    Big data analytics uses and examples

    Insights business users extract from relevant data can help organizations make quicker and better decisions. The benefits of using big data analytics include. ... Rapidly making better-informed decisions for effective strategizing, which can benefit and improve the supply chain, operations and other areas of strategic decision-making. ... Big data analytics involves analyzing structured and unstructured data.
    customer acquisition | tool | data security | engineer | marketing | purchase | network

    History and growth of big data analytics

    Initially, as the Hadoop ecosystem took shape and started to mature, big data applications were primarily used by large internet and e-commerce companies such as Yahoo, Google and Facebook, as well as analytics and marketing services providers. ... Users include retailers, financial services firms, insurers, healthcare organizations, manufacturers, energy companies and other enterprises.
    story telling | energy company | software tool | financial service | insurance company | health care | marketing
    Example of a summary
    (divided into plausible
    Parametrization of the Web-App

    Pricing Plans

    Business Models

    for individual users
    • only URLs
      (no document uploads)
    • public server
    • document size < 5MB
    • no Support
    • 1 month FREE
    for individual users
    • Full Access
    • public server
    • document size < 5MB
    • 1 Month Support
    • monthly 20

      40 € for unlimited docsize
    for companies
    • Full Access
    • private server
    • document size unlimited
    • 1 Month Support
    • monthly max. 10

      per Employee
    for developers
    • Full Access
    • private server
    • document size unlimited
    • 1 Month Support
    • individual Prizing
    Our Contact

    Get In Touch.

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    CH-9470 Buchs SG

    +41 81 750 5300

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