“Do you review masses of pleas or contracts on the same topic every day?”
“Do different wordings make automation impossible?”
“Does correspondence with companies, clients and insurance companies determine the further course of proceedings and cause high manual effort?”
This is exactly where our AI semantha® can help: It understands text based on meaning, regardless of word choice – so you can find content you’re looking for no matter how it’s worded – out of the box and without extensive training with your data.
The most frequently implemented use cases in legal.
In your company masses of correspondences have to be processed and allocated every day. Each mail must be analysed at great expense before the next step can be taken. It is quite possible to assign certain categories, but the problem is that similar facts are formulated very differently, which apparently makes it impossible to automate this process.
In your company, many procedures on the same topic are processed. Despite always having similar presentations in the pleas and repetitive correspondence with companies, insurers and clients, these documents have to be read and analysed at great expense. Although content can be divided into certain categories, the problem is that similar issues are formulated in completely different ways, which makes it seem impossible to automate the processes.
You have to reply to numerous pleas, such as lawsuits or statements of defence, and repeatedly come across similar submissions. In most cases, you can use excerpts from past responses as a basis for the new plea. However, the classification of the individual submissions of the newly received pleas is the biggest challenge.
In your company, contracts have to be reviewed regularly and with a high manual effort. In most cases, the content to be reviewed is similar. The problem is that every contract is worded and structured differently, which makes automation impossible.
Harmonization of company-wide regulations, such as company agreements, work instructions & SOP’s across different locations
With semantha® we have developed an AI tool that overcomes the weaknesses of conventional matching tools. The application does not compare whether certain terms occur in documents, but reads the documents at the level of meaning. And it does so within a few moments.
Your company has large masses of unstructured text documents. One of the daily challenges is to search these documents for specific content, whereby normal search functions only offer a simple “keyword search” that does not lead to the desired results. This is particularly due to the fact that, on the one hand, it is not known exactly how a topic was formulated and, on the other hand, the same topics are also formulated quite differently in the various documents.
You don’t see a contact form? Then you have probably rejected cookies. However, the form requires cookies. You can change your settings here: Change cookie settings.
R+V has been the insurance expert in the Volksbanken Raiffeisenbank cooperative financial group since 1992.
Die Mercedes-Benz Group AG ist ein börsennotierter deutscher Hersteller von Personenkraftwagen und Nutzfahrzeugen, der auch Mobilitäts- und Finanzdienstleistungen anbietet.
Behr-Hella Thermocontrol GmbH is a company founded in 1999 for the development and manufacture of air conditioning control units for automobiles and other vehicles.
BLOG
Success stories with our clients
City of Heilbronn has central incoming mail processed using AI
Compliance management: methods, tools and trends
Legal clarity at the push of a button: Volksbank checks interest rate clauses with AI
CV matching: The best applicants with one click
Did you know? Interesting facts or figures about artificial intelligence