• AI Projects with practical Experience

Place a document in the business domain of Legal

Place a document in the business domain of Legal

Project Profile

Filing a document. With this project we show that it is possible to learn documents of different origin and type from a filing system in a secretary's office (default to filing) and to apply it to new documents. In this way, the secretary's office can be relieved of workload and the customer can be oriented to the filing requirements of the person requesting the documents.

At a glance - essential project data

DurationFrom 12/1/2018 to 12/1/2018 with about 2 months of full engagement
Data and ToolsMarket - Legal
 • Exports from customer DB
 • 250 real documents
 • Generation of 10,000 synthetic documents
IntegrationWeb API for metadata enrichment with model-generated data to be passed to the production system
AI Methods • NLP
 • Deep-Learning
 • Heuristics
 • ML-Statistics

Engagement Use-Case

Filing of documents according to their individual filing date in the secretary's office.

Client motivation / Solution aims

  • Replication of human filing characteristics of documents in a law firm

AI Approach

AI key technology used in our solutionMultiple dates (approx. 20 dates) per legal document possible. Find the right date and put it on the "learned" push - trained unsupervised as a whole.
Solution Approach • NLP
 • Deep-Learning
 • Heuristics
Project ApproachSimply agile
Project TypeProof-Of-Concept (POC)
ML Integration and ML Operations • Operation Integration API
 • VIsualizationAPI

Insights and Details

Multi-Model Approach Model 1 Results

Multimodel Approach Model 2 Results

Multimodel Approach Model 3 Results including Topic Modeling to identify the topic Cluster of a Document. Learning with topcis and derived rules is easy!

Evaluation with a Deep-Learning Approach to identify the best result of a model. Working with all Models to get the best results.

Showing the difference between model results and joint model results.