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ABOUT NORCOM

Instead of manually capturing information from documents, emails or notes, leave the research and information extraction on a case to DaSense. You only check the result of the AI and thus have more time for the qualitative support of the customer. 

The task

Invoices must be checked for consistency and abnormalities such as double bills must be made visible. As a complex manual process, this should be automated to the greatest possible extent; through the use of advanced analytics, even rare and complex abnormalities should be easy to find.

 

The challenge

Invoices were available in scanned form with different scan quality, the number of pages and order were variable, the information contained therein was both structured (tables) and unstructured (free text), both with strong structural variations.

our solution

We created a pipeline consisting of OCR, table recognition and information extraction. An integral part of the pipeline was an automatic evaluation of the quality of the extraction results with the possibility of controlled optimization. Invoices were merged through the detection of close duplicates and duplicate entries and other anomalies were made visible using advanced analytics. A scalable architecture makes the functionality of the pipeline visible even on large data and enables the analysis of statistical anomalies.

The customer benefit

Thanks to automation, only a few invoices need to be checked manually, which leads to significant time and cost savings. The detection rate of abnormalities is significantly increased thanks to advanced analytics.

App Ingest.png

What sounds banal at first glance poses problems for many AI users in practice: the heterogeneous, distributed data must be made available to the AI system in a form that can be evaluated. Ingest-App reliably takes care of this.

 

Functions: Recording of all file types, creation date, authors, mdf ingest, preparation for full-text search, deduplication, multidimensional filing, information extraction

Currently in use, e.g., in the measurement data analysis in the development department of an automobile manufacturer

App dashboard.png

This app is your control center: The dashboard shows various visualizations and enables aggregated views of the data. Whether interactive evaluation or the consideration of sub-areas - the dashboard app provides central insights.

Functions: visualization, index-based technologies, interactive evaluations and work with the data, combination of filters.

Currently in use , among other things, in the monitoring of production processes

APP detection.png

Mistake, goodbye! Detection searches huge datasets for anomalies. Through correlation analysis, Detection not only finds the errors, but also the reasons for them.

 

Functions:Ttime series analysis, event search, combined analysis of logs and traces, creation of snippets, correlation analysis

Currently in use, e.g., in the evaluation of abnormalities in the measurement data of automotive test fleets

Your advantages with DaSense

tested

Organization

- any order Dimensions

DaSense offers multidimensional storage structures, so-called facets, which can be combined and filtered as desired. There are also clear annotations for documents and clear versioning.

Features:

  • Property facets: Multidimensional filing structure based on document properties such as language, document type, etc.

  • Workflow facets: Multidimensional storage structure according to processing status, evaluation, etc.

 

  • Annotations: Linking properties to individual parts of the document, i.e. sentences, sections or images 

Advantages

  • Supplementing the existing folder structure with practically relevant categories

  • Illustration of complex relationships

  • Linking multiple facets

Organization

- any order Dimensions

DaSense offers multidimensional storage structures, so-called facets, which can be combined and filtered as desired. There are also clear annotations for documents and clear versioning.

Features:

  • Property facets: Multidimensional filing structure based on document properties such as language, document type, etc.

  • Workflow facets: Multidimensional storage structure according to processing status, evaluation, etc.

 

  • Annotations: Linking properties to individual parts of the document, i.e. sentences, sections or images 

Advantages

  • Supplementing the existing folder structure with practically relevant categories

  • Illustration of complex relationships

  • Linking multiple facets

Your individual processes can be mapped using flexible AI apps

Legally secure

DaSense follows all common legal requirements. Results of the AI are understandable.

 

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