• Data mining (text+image recognition)
  • Data processing (aggregating, classificating, filtering, searching)
  • Data management tools (GUI for data management)
  • Data labeling tools
  • Forecasting models
  • Workflow optimization

Problems we solve:

  • Data in paper documents is hard and slow to derive
  • Papers require a lot of hand labour and human resources
  • Digitized documents contain lots of mistakes

ARKEDA builds solutions helping you automatically process paper documents of any kinds, store and analyze data and save resources and time!

Our solutions:

Non-Compliance Reporting & Risk Management

A personal assistant on maintenance for oil&gas industry

We can help you digitize a database of oil&gas technical documentation, to let AI automatically search through it and advise a user how to solve issues and industrial incidents, and take better decisions.

Kundendialog- & Ereignis­management

Medical e-card

We have built an app that can store and share with a doc patient's test results and CT/MRI scans, etc. The app can give recomendations for various conditions.

Doctors get an access to the data labeling tool helping the app better diagnose conditions.

Bulding plans and other documentation

We digitize archives of paper documents

We have built an interface letting users upload files, derive texts and schemas out of them and save it in a database. Apart from search and filtering procedures, a user is allowed to create and edit mockups for automatic text/image recognition when the document type is known. Moreover you can find the documents that are related to each other by the parameters of your choice.

Our projects

eInvoice ML Module

ML module for invoice conversion from PDF file to XRechung and PEPPOL BIS invoice formats.

Chemical Database

ML module for chemical database was developed in cooperation with Webware Inernet Solutions Gmbh on behalf of Wintershall Dea GmbH

Medical E-Card

E-Card App can store and share with a doc patient's test results and CT/MRI scans.

eArchive ML Module

ML module extracts information from scanned documents, finds keywords and creates meta information for storage in the electronic archiving system