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.
AI-native SaaS dashboards with a data advisor
AI Agents, Apps & Web Development Studio
Product systems and software architectures with Google Agent Development Kit (ADK), React Native & React
AI-native SaaS dashboards with a data advisor
An AI-native SaaS dashboard explains product data, segments, and anomalies and prepares next steps in a reviewable product surface.
What this is for
This fits SaaS products where teams need to understand what changed, which users or segments are affected, and which action makes sense now.
The dashboard becomes a workspace where metric, segment, cause, source, recommendation, correction, and prepared action sit side by side.
appamass connects React/Vite dashboards, TypeScript data contracts, and Agent Development Kit (ADK)-based agents so analysis, recommendation, and approval work as one product system.
The first useful build explains one critical metric or segment clearly enough for users to inspect the source, assumption, and recommended action.
Turn product data into understandable next steps
A dashboard should not stop at charts. It should answer what happened, who is affected, why it likely happened, and which action can be prepared.
What users see
Users see metrics, segments, trends, charts, sources, anomalies, forecasts, recommendations, scenarios, and forms for next steps.
How it works
React/Vite, TanStack Query, Tamagui tables, Cloud SQL or Firestore, analytics data, retrieval, Agent Development Kit (ADK) or Vertex AI logic, roles, backend APIs, tests, and monitoring work together.
What stays controlled
Data quality, segment definitions, sources, recommendation rules, corrections, roles, error states, monitoring, and measurement after action stay controlled.
A first SaaS data advisor inside the dashboard
The first slice should improve one real metrics area: detect, explain, review, and only then act.
Make metrics and segments understandable
Metrics, segments, and time windows get clear definitions, readable display, and visible data sources.
Explain anomalies
Changes are shown with comparison values, possible causes, sources, and uncertainty.
Prepare actions
Recommendations become forms, tasks, or approvals users can correct and later compare with outcomes.
Other services
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.