AI Agent Development
AI agent development becomes useful when an agent does more than answer: it uses sources, tools, rules, and approvals to complete a task.
Product systems and software architectures with Google Agent Development Kit (ADK), React Native & React
Controlled document workflows help with documents that need to be uploaded, extracted, reviewed, commented, enriched, and approved.
This use case fits when documents are uploaded, fields are detected, rules are checked, and approvals need a traceable audit trail.
A document workflow turns upload, extraction, review, correction, and approval into one controlled path.
appamass connects Agent Development Kit (ADK)-based extraction and review agents with React/Vite review surfaces and TypeScript contracts so every change stays visible.
The start should take one document type through required fields, source snippets, correction, comment, and approval.
Document work becomes risky when extraction, comments, and approvals are split across tools. A controlled workflow keeps source, field, decision, and export together.
Users see upload status, extracted fields, source passages, missing information, comments, and review decisions.
Document parsing, source matching, structured fields, React/Vite review surface, Cloud SQL or Firestore for review history, roles, and exports connect behind the workflow.
Document versions, extracted fields, manual corrections, roles, audit trail, export formats, and retention stay controlled.
The start should carry one document type through the full path: upload, extraction, review, approval.
One document type gets required fields, source passages, rules, and error cases.
Extracted fields show original passages, comments, and correction options.
Approvals, changes, users, and exports are logged in a traceable way.
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.