Selected work
Architecture, decisions, and outcomes—not just screenshots.
Our case studies show how a problem becomes an engineered system, with transparent detail about the approach and technology.
AGENTIC / WORKFLOW / 001
Multi-Agent Content Orchestration Pipeline
Challenge
Automating the research, writing, and review process for large-scale content generation.
Approach
Orchestrated CrewAI and Claude to create distinct agent roles (Researcher, Writer, Editor).
Architecture
Stateful agent workflow built with LangGraph for observable, multi-step execution.
Stack
Python · LangGraph · CrewAI · Claude API
SYSTEM / UI / 002
Sanrid Systems Platform Architecture
Challenge
Build a highly performant, SEO-optimized agency website that seamlessly integrates with backend AI services.
Approach
Adopted TanStack Start for unified frontend/backend SSR rendering and strict type safety.
Architecture
Vite + Nitro deployment to Edge networks with an integrated React component library.
Stack
React · TypeScript · TanStack · Nitro
APP / AI / 003
Constitutional AI Chat Interface
Challenge
Provide a conversational interface with absolute strict safety guardrails and boundary adherence.
Approach
Implemented a UI clone of ChatGPT backed by constitutional AI principles.
Architecture
React frontend streaming SSE responses from a heavily guarded Python backend.
Stack
Next.js · Python · LLMs · Streaming
ENGINEERING / AUTOMATION / 004
N8N Webhook Automation Pipeline
Challenge
Connect disjointed SaaS applications to trigger data synchronization without human intervention.
Approach
Built a visually mapped node workflow to catch webhooks, process JSON data, and update databases.
Architecture
N8N self-hosted instance managing robust retry logic and third-party API rate limits.
Stack
Node.js · N8N · Webhooks · REST APIs
KNOWLEDGE / RAG / 005
Enterprise Knowledge Retrieval System
Challenge
Surface specific operational context from thousands of raw internal PDF documents and wikis.
Approach
Implemented an advanced RAG (Retrieval-Augmented Generation) pipeline using semantic vector search.
Architecture
Python microservice generating document embeddings and storing them in a high-speed vector database.
Stack
Python · LangChain · Vector DB · LLMs
CONCEPT SYSTEM / 002Enterprise knowledge retrieval assistant
Document ingestion, grounded answers, citations, access-aware retrieval, and evaluation.
CONCEPT SYSTEM / 003Agentic operations workflow
Goal interpretation, tool use, approval gates, execution, and observable outcomes.