Natural-language questions over APIs and databases, safely

For teams that want self-serve data access without opening SQL or admin APIs, appamass builds gated natural-language gateways with read scopes, audit logs, and human approval before any write or sensitive export.

  • Secure natural language interfaces and database gateways with strict enterprise guardrails for relational data and API access.

  • appamass connects Google Agent Development Kit (ADK)-based agents, Python, query guards, TypeScript contracts, and React/Vite review surfaces so natural language access keeps clear guardrails.

  • The first gateway slice defines allowed tables, filters, roles, and forbidden operations before write actions are even considered.

Translate questions into safe data access

Natural language is convenient, but data access needs boundaries. The gateway turns questions into safe queries and separates reading, suggesting, and changing.

What users see

Users see prompt, result list, source rows, generated filters, prepared change, and clear error messages.

How it works

Query guards, API contracts, schema context, Cloud SQL/PostgreSQL, IAM boundaries, retrieval, review surface, and audit logs connect behind the gateway.

What stays controlled

Allowed tables, filter limits, write rights, query cost, result quality, logs, and approvals stay controlled.

A first data gateway

The first build should solve one safe read question and only then prepare controlled changes.

Define query boundaries

Allowed data areas, roles, filters, and forbidden operations are explicit.

Build safe summaries

Results show source rows, filters, uncertainty, and readable explanation.

Review changes

Updates are shown as suggestions and require validation, role, and approval.

Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.

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