Everything here is rule-based: values are substituted into your own approved file, and every finding is proved from the text itself. The same input always gives the same result.
What it has learned here, and teaching it a new type from approved examples.
Authorization Letter - othersYurtec
6 fields · learned from 2 examples
Application to RJSCYurtec
2 fields · learned from 4 examples
Authorization Letter - BIDAYurtec
9 fields · learned from 3 examples
Authorization Letter - othersJGC Corporation
10 fields · learned from 4 examples
Application to RJSCJGC Corporation
2 fields · learned from 4 examples
Authorization Letter- BIDAJGC Corporation
8 fields · learned from 2 examples
Application to RJSCFUJITA CORPORATION
2 fields · learned from 2 examples
Application to RJSCCOLGIS BD Ltd
4 fields · learned from 2 examples
Notice Minutes of BM for address changeCOLGIS BD Ltd
8 fields · learned from 2 examples
Form VICOLGIS BD Ltd
9 fields · learned from 3 examples
Notice Minutes of BM for Address ChangeBangladesh Japan (BJCC)
4 fields · learned from 2 examples
Notice & Minutes of BM for address changeAI SAMURAI JAPAN Limited
16 fields · learned from 4 examples
Form VIAI SAMURAI JAPAN Limited
6 fields · learned from 4 examples
Authorization LetterAI SAMURAI JAPAN Limited
14 fields · learned from 4 examples
Application to RJSCAI SAMURAI JAPAN Limited
10 fields · learned from 4 examples
Pick two or more approved documents of the same kind that differ only in their details — three notices for different shareholders, say. Comparing them shows which parts are the format and which are the facts. The first one you tick is the base, and every draft is built from that exact file, so drafts keep its letterhead and layout.