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
A spatial and asset inspection agent connects photos, location, asset data, manuals, risk hints, and follow-up tasks in a mobile inspection flow.
This fits inspections where photo, location, asset data, history, and follow-up task belong together immediately.
An asset inspection flow connects evidence, place, object, risk, and action in one mobile review.
appamass combines React Native/Expo, TypeScript contracts, backend data, and Agent Development Kit (ADK)-based agents when mobile capture and later review need to fit together.
The first slice should make one inspection traceable from captured evidence to follow-up action.
Inspections improve when evidence is immediately connected to the right object. The flow should show what was seen, what it belongs to, and what follows.
Users see photo, location, asset metadata, checklist, sources, risk hint, and suggested action.
React Native/Expo, camera, maps, asset database, retrieval, risk scoring, Firebase/FCM, backend APIs, and logs connect behind it.
Photo and location data, asset matching, checklists, risks, approvals, follow-up tasks, and audit trail stay controlled.
The first build should make one inspection traceable from photo to action.
Photo, location, time, user, and asset context are saved together.
Checklist, history, manual passages, and risk hints support the assessment.
Repair, escalation, or further review is prepared with context and owner.
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.