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)