Justin · AI Platform & Agentic AI Engineer

Turn frontier AI intosystems that actually run.

Agent, RAG, and AI Platform engineering: architecture, evaluation, deployment, operations, and handoff.

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Engineering workflow Documents → Retrieval → Agent → Evaluation View workflow details
01INGEST

Document Parsing

PDF · OCR · Table structures

02RETRIEVE

Hybrid Retrieval

BM25 · Dense · Re-ranking

03AGENT

State Machine & Tools

LangGraph · Intent routing

04EVAL

Benchmark & Tracing

98.0% accuracy · Observability

Engineering workflow diagram

PIPELINE // ARCHITECTURE PROD-VERIFIED
01 INGEST

Document Parsing

PDF · OCR · Table structures

02 RETRIEVE

Hybrid Retrieval

BM25 · Dense · Re-ranking

03 AGENT

State Machine & Tools

LangGraph · Intent routing

04 EVAL

Benchmark & Tracing

98.0% accuracy · Observability

Engineering workflow diagram

Flagship system: a measurable Agentic RAG pipeline

From 'a chatbot that can retrieve' to a measurable, deployable, and controllable enterprise knowledge base agent

Agentic RAG System

Problem
Mixed enterprise documents and unstable user phrasing made conventional RAG miss or mis-rank critical instructions.
Method
Built a controlled LangGraph workflow with rule-first routing, hybrid retrieval, context validation, and retries.
Outcome v22 weighted accuracy 98.0%; rule-first avg latency 2.606s.
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More engineering case studies

PaddleOCR · YOLOv7 · Hospital Receipt Structuring · End-to-end Normalization

Receipt OCR API

Outcome Normalized formats from 5+ hospitals into API-ready JSON.
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Start with the question closest to yours

  1. 01 How do enterprise Agents stay controllable? Design evaluation, observability, permissions, and failure recovery into Agent workflows so they can be inspected and operated.
  2. 02 How can retrieval be made reliable? Turn scattered documents, permissions, and difficult queries into retrieval systems with measurable quality and traceable answers.
  3. 03 Need a technical talk or architecture exchange? Use an architecture review, PoC evaluation, or engineering talk to clarify the next decision for your team.

Speaking / Exchange / Collaboration

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