SYSTEM_STATUS: AUTONOMOUS

NEURAL
ORCHESTRATION.

I architect the Central Nervous System of your business. Autonomous Agents and Self-Healing Workflows that bridge the gap between your Raw Data and AI Models.

24/7OPERATION

<200msLATENCY

100%OBSERVABILITY

EXECUTION_LOGLIVE

1.0 // The Automation Stack

COGNITIVE PIPELINES

01 // VECTOR INGESTION

Automating the "Learning" process for AI. I build workflows that watch Google Drive, sanitize documents, compute OpenAI Embeddings, and upsert them into Pinecone without human intervention.

Tech: Pinecone, OpenAI, Vectors

AGENTIC LOGIC

02 // PROTOCOL-BASED AGENTS

Moving beyond simple prompts. I design LangChain Agents with strict "Protocols" (Sales, Support, Lead Capture) ensuring the AI adheres to business rules and uses tools correctly.

Tech: LangChain, Tools, JSON

SYSTEM INTEGRATION

03 // DYNAMIC LOGGING

Every interaction is data. I build self-maintaining logging systems that create new Google Sheets tabs dynamically based on date/config and append structured session logs.

Tech: Google APIs, Webhooks, HTTP

2.0 // Case Studies

PROJECT SYNAPSE

THE LIVING KNOWLEDGE BASE

The Challenge: AI models are useless if their data is old. The client needed a way to "teach" the AI new policies instantly by just dropping a PDF into a folder.

The Architecture: A webhook-triggered flow that lists files from a Google Drive Inbox. Custom JS nodes convert Docs to text while handling PDFs as binaries. Before upserting, we delete old vectors to prevent "Ghost Data".

"I don't just copy files. I manage Vector Lifecycles."

smart_binary_handler.js

if (!item.binary && item.json.data) {
  // Handle Google Doc Export
  const textContent = item.json.data;
  item.binary = {;
    data: Buffer.from(textContent).toString('base64'),
    mimeType: 'text/plain',
    fileName: original.name + '.txt'
  };
} else {
  // Handle Native Binary (PDF/IMG)
  item.binary.data.fileName = original.name;
}
return $input.all();

PROJECT NEXUS

THE OMNI-AGENT BACKEND

The Challenge: Standard chatbots hallucinate. The client needed a bot that acted like a trained Sales Rep.

The Architecture: A LangChain Agent with 4 distinct Protocols (Consult, Product Search, Info, Closing). The agent autonomously decides when to query the Inventory DB or capture lead data into Sheets.

Protocol Enforcement: Strict System Prompts prevent off-topic chatter.
Tool Orchestration: Autonomous JSON-based tool calling.
Hybrid Output: Returns Text + UI JSON for frontend rendering.

USER CHAT

LangChain Agent

Protocol 1: Consult

Protocol 2: Search

Protocol 3: Capture

JSON UI

Inventory DB

Google Sheets

Visual Evidence

Production workflows and interfaces running in the wild.

RAG Ingestion Flow

Chat Interface

NEURALORCHESTRATION.