Automotive Supplier
Requirements & Specification Analysis
Requirements specifications and requirements have to be checked regularly with high manual effort and time pressure. Many requirements and clauses differ only slightly in content from those from projects that have already been completed – nevertheless they have to be read and evaluated again and again.
Correspondence Automation
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.
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With semantha® you can automatically classify and assign incoming letters, no matter how they are formulated, regardless of the choice of words.
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With our data extraction, you can easily extract relevant data points from Correspondences and process them further. The combination with semantha’s® natural language understanding is particularly helpful, as it allows you to find and extract data points in specific contexts.
OEM and Supplier Contract Analysis & Comparison
In your company, Framework contracts of OEM customers 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.
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In our library, you can define content for which new incoming contracts should be checked. semantha® finds the passages based on the meaning, independent of the word choice and completely without “training” with your data. This way, the appropriate response is quickly found for every submission.
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Using our Compare, you can compare previous correspondence with new incoming correspondence. semantha® shows you which contents match and which contents are missing – out of the box and without time-consuming training with your data.
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In addition, you can use our Compare feature to compare different versions of a contract. semantha® shows you which contents have remained the same and which areas have been changed or removed completely.
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With our data extraction, you can easily extract relevant data points from documents and process them further. The combination with semantha’s® natural language understanding is particularly helpful, as it allows you to find and extract data points in specific contexts.
These use cases might also interest you…
Alignment of standards
The necessary comparison with internal and external standards (e.g. norms, applicable documents and industry standards) is taken into account by semantha® during the requirements analysis.
Consolidation of documents
Harmonization of company-wide regulations, such as company agreements, work instructions & SOP’s across different locations
CV Matching
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.
- Ranking of top candidates at the touch of a button
- Overview of the best internal candidates for any skills
- More objective selection of candidates
- Acceleration of the selection process by up to 50%
- More time for interviews to ensure human fit
Tender Analysis
In your company, tenders have to be checked and evaluated regularly and with a high manual effort. In most cases, the content to be reviewed is similar. The problem is that every tender is worded and structured differently, which makes automation impossible.
Knowledge Management
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.
