Technology Stack

Cloud Architecture & Graph Models

Explore the underpinnings of our platform. From event-driven queues to dense vectors and schema graphs.

Dense Vector Graph Extraction

We convert unstructured textual nodes into multi-dimensional embeddings via dense models. These vectors are mapped onto a persistent schema graph to preserve semantic relationships.

Our vector index runs inside a Qdrant cluster on private cloud architecture, providing sub-150ms search latencies over millions of nodes.

Architecture Topology

Incoming Traffic → CDN Cache (Vercel edge)

→ API Gateway → Authentication Layer (OAuth)

→ Queue Broker → Ingestion Normalizers

→ Dense LLM Parser → Qdrant Vector Engine

→ Audit Compliance Engine → Database (PostgreSQL)