Logical Architecture
Multi-tiered, event-driven system optimized for low-latency reads, high-throughput writes, and deterministic AI inference.
Web / Mobile
React Native / PWAAPI Clients
REST / GraphQL / gRPCAdmin Portal
Internal DashboardsEdge Network
CDN / WAF / DDoS ShieldAPI Gateway
Rate Limiting / Auth / RoutingSearch Service
Semantic / KeywordAI Engine
RAG / LLM OrchestrationContent API
Versioned / StructuredVector DB
Embeddings / SimilarityDocument Store
Markdown / JSON-LDCache Layer
Redis / CDN EdgeCore Components
Modular microservices designed for independent deployment, horizontal scaling, and fault isolation.
Edge & Delivery Layer
Global CDN with intelligent caching strategies, edge computing for request transformation, and automated DDoS mitigation.
API Gateway & Auth
Centralized routing, JWT/OIDC authentication, API versioning, rate limiting, and request/response transformation.
AI & RAG Pipeline
Retrieval-Augmented Generation with hybrid search, citation grounding, hallucination filtering, and multi-model routing.
Data & Storage Layer
Partitioned document store, vector embeddings for semantic search, immutable versioning, and automated schema validation.
Observability
Distributed tracing, structured logging, real-time metrics, alerting, and SLO/SLI tracking across all services.
Event Bus & Sync
Asynchronous message queue for content updates, cache invalidation, AI retraining triggers, and audit logging.
Query Processing Pipeline
Step-by-step execution flow from user request to validated knowledge response.
1. Request Ingestion
Client request hits the edge network, undergoes TLS termination, WAF inspection, and is routed to the nearest availability zone.
2. Authentication & Rate Control
JWT validation, API key verification, tenant isolation, and adaptive rate limiting based on user tier and historical patterns.
3. Cache Lookup (Hot Path)
Multi-tier cache check (L1 in-memory, L2 Redis, L3 CDN). If hit, returns serialized JSON-LD with citation metadata.
4. Semantic Retrieval & AI Synthesis
Query embedded via transformer model, vector similarity search executed, top-k documents retrieved, LLM generates grounded response with strict citation constraints.
5. Validation & Response Assembly
Fact-checking layer verifies claims against primary sources, JSON schema validation ensures structural compliance, response cached and streamed to client.
Technology Stack
Production-grade technologies selected for performance, maintainability, and ecosystem maturity.
| Category | Technologies |
|---|---|
| Languages | TypeScript, Go, Python, Rust |
| Frontend | Next.js, React, Tailwind CSS, TanStack Query |
| Backend | NestJS, Go (Gin/Fiber), FastAPI |
| Database | PostgreSQL, CockroachDB, Milvus, Redis |
| Search | Elasticsearch, pgvector, Hybrid Retrieval |
| AI/ML | LangChain, vLLM, HuggingFace, ONNX Runtime |
| Infrastructure | Kubernetes, Terraform, Helm, ArgoCD |
| Observability | OpenTelemetry, Prometheus, Loki, Grafana, Datadog |
| CI/CD | GitHub Actions, Argo Workflows, Trivy, SonarQube |
Scalability & Security Posture
Built for global throughput with defense-in-depth security and strict compliance boundaries.
Security Controls
Zero-trust network, mutual TLS between services, secrets management via Vault, automated vulnerability scanning, RBAC with least-privilege enforcement, and encrypted data at rest & in transit.
Disaster Recovery
Multi-region active-active deployment, automated failover, continuous backups with point-in-time recovery, chaos engineering drills, and RTO/RPO targets of <5min / <1min.