The development environment is based on Ephesoft Software. The rules or codes are based on the classification of the documents, and batch classes are created after the classification for the documents. Each document is indexed, where extraction rules are established. There are three types of extraction:
We used Regular Expression (Regex) in the rule set-up. Ephespoft Software supports our dictated rules to jumpstart the desired extraction.
An administrator acts as the Quality Analyst is required to validate extracted data, ensuring it aligns with the customer’s requirement. If the desired extraction is not cohesive then the administrator reassigns the work to a Data Extraction team who manually completes the processes.
For data extraction approved by the administrator, the corresponding output is imported into the immediate extracting system and is followed by data transformation and possibly the addition of metadata prior to exporting to another stage in the workflow.
Multiple users can access the extraction and validation. Once multiple sample files are provided to create extraction rules in one format, the rules can be applied in an automated extraction. Each desired extraction must be written into a rule requirement to operate sufficiently. Our client provides documents that list all the “document types” and “fields” to be extracted. The enumerations are built into the system so that the extractions can be obtained with greater accuracy. Regex library accommodates all possible fields, and the “document types” are described by annotations within the document.
Ultimately, the Ephesoft Software becomes more attune to the client’s needs as time passes. With RPA technology, the software has to be “trained.” The client has been able to train our software effectively improving nearly every facet of their infrastructure and rendering repetitive, manual processes obsolete. Our relationship with this client has carried on far past this project—our collaborative RPA work has transitioned into a long-term partnership.