Case StudySecure data platform

TwinVault - secure AI-enhanced asset platform

Secure storage and management for digital assets and credentials with privacy-focused architecture.

Role-aware asset and credential controls

Role

Founder and platform architect

Team context

Founder-led product and platform build executed through Twindevs with direct ownership of architecture and implementation direction.

Responsibility scope

Defined the secure asset-management product shape and full-stack architecture.
Designed RBAC, lineage, and lifecycle controls across sensitive records.
Set the service boundaries between Next.js, FastAPI, PostgreSQL, and AI integrations.

Stakeholders

Decision points

Use PostgreSQL plus pgvector for structured metadata and retrieval rather than splitting core state across multiple stores.
Treat lineage and lifecycle controls as first-class product features instead of compliance afterthoughts.
Keep AI integration behind a gateway boundary so provider changes do not leak into the core asset model.

Problem and constraints

Create a secure platform for managing sensitive digital assets and credentials with clear ownership and lifecycle controls.

Architecture approach

Next.js frontend and FastAPI gateway with an AI integration layer using Vertex AI and fallback provider support.
PostgreSQL plus pgvector-backed data storage with structured metadata and retrieval support.
RBAC, encrypted lineage tracking, and lifecycle controls across assets, credentials, and documents.

Outcomes

Consolidated asset and credential management into one structured system.
Introduced role-aware controls and audit-friendly lineage for sensitive records.
Improved maintainability with a clear full-stack architecture boundary.

Next iteration

Add policy-based validation checks to continuously verify access boundaries and data handling assumptions.