Deep Dive

Architecture

Explore the technical pipelines powering production AI systems

Every system is designed for observability, graceful degradation, and horizontal scaling. Pipelines are modular--swap any component without rewriting the orchestration layer.

Advanced RAG Pipeline

Q

User Query

Natural language input from the user

R

Query Rewrite

Expand & disambiguate using LLM

S

Hybrid Search

BM25 keyword + dense vector retrieval

K

Rerank

Cross-encoder reranking for precision

C

Context Assembly

Merge top-k chunks with metadata

G

LLM Generation

Generate grounded answer with citations

Agentic Loop

Plan

Decompose task into sub-goals with dependency graph

Act

Execute tools & API calls based on the current plan

Observe

Evaluate tool outputs and update internal state

Correct

Self-critique, backtrack if needed, and re-plan

Continuous loop until goal is met

Infrastructure Overview

Compute

  • AWS Lambda
  • ECS Fargate
  • SageMaker Endpoints

Storage

  • S3 Data Lake
  • Pinecone Vector DB
  • DynamoDB
  • ElastiCache

Orchestration

  • Step Functions
  • EventBridge
  • SQS / SNS
  • CloudWatch