Our Products.

Our AI based software plattform currently consists of three core areas of knowledge and data management.

Fully automated batch processing

Based on the frequent delivery of content in a variety of formats and methods.


Through:


  • Extraction of specific content, transfer to a desired data repository,
  • marking of characteristics such as criticality or relevance so that processing by employees can be better controlled,
  • automated postings that were previously processed manually due to complex interrelationships.

Content
editing

to be able to process specific enquiries effectively.



Examples:


  • Supporting ‘support teams’ by categorising the context of the enquiry and providing suitable answers,
  • creation of new customer offers by directly identifying suitable products,
  • exclusive processing of new or contradictory content by automatically identifying older and therefore already processed context.

Making
decisions

Based on current and previous content usage.



Through:


  • Quick access to repositories across application boundaries,
  • extensive filter functions, especially for unstructured content,
  • the use and linking of causal relationships.

Product #1: Content.Flow

Using no-code definitions, the central content utilisation of unstructured data and the processes can be formulated by the department itself, MaRisk and ISO 27001 compliant.

Pre-processing and structured results are generated reliably via batch processing and AI integrations.


Content.Flow do address this uses cases:

Automated processing

Examples:

  1. Create a knowledge database based on existing and changing content initially
  2. and keep it up to date.
  3. Forward incoming emails from a collective address to the correct department
  4. based on the content.
  5. Check whether the e-mail comes from an existing customer and add content.


Solution & benefits:


  • Any sources (e-mail, folders, applications) can be connected.
  • Updates in the sources automatically update the filing system.
  • The language understanding of AI is already applied in pre-processing (subject of the enquiry).
  • Existing repositories can be used for validations (customer name, e-mail address, ...).
  • The results of processing can be transferred to common repositories (DB, API, etc.).


Content-based actions

Examples:

  1. Public opinions on regulatory developments and topics should be regularly recognised and lead to automatic internal notifications.
  2. Own content (example: documentation) should be checked and, if necessary, edited linguistically.


Solution & benefits:

  • Regular surveys lead to known and standardised processes.
  • Known procedures in scenarios prevent regular ‘reinvention’.
  • The effects of measures could be recorded in a structured manner and made measurable.


Information extraction

Examples:

  1. The aim is to recognise and extract defined content from external documents (unknown display format, e.g. term sheets,
  2. invoices, quotations, etc.).
  3. A ticket enquiry is assigned to a known customer and enriched with important content.
  4. An upcoming action (project, surgery, ...) is to be supplemented with essential information from a large amount of data.


Solution/ benefits:

  • Semantic capabilities of AI enable format-independent processing.
  • Intermediate steps and time-consuming diligence through manual processing by the
  • expert are reduced and enable focus on the core topic of the enquiry.
  • The degree of digitalisation of the company is increased, as even unstructured content can be transferred to a standard process.


Knowledge - Conservation and utilisation

Examples:

  1. The contents of the knowledge database should be made available to employees or customers as a dialogue system.
  2. During the creation of new content (example: doctor's letter), the user should be shown suggestions for more efficient creation based on company knowledge.


Solution & benefits:

  • Knowledge that was previously inaccessible or difficult to access can be reused in a standardised way.
  • Central contact points with high quality lead to acceptance and reduce cost-intensive 1:1 responses.
  • The quality of specialised content is significantly increased.