Practical AI systems, end to end

Hi, I'm [Your Name]. Fullstack AI Engineer building practical AI systems for real-world business workflows.

I design and develop AI-powered applications involving RAG, OCR, computer vision, LLM automation, backend systems, and production-ready dashboards.

My work focuses on turning messy data and manual workflows into reliable AI-assisted systems.

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System Map

AI workflow readiness

MVP to Prod

Workflow

Data

Retrieval

Model

API

Dashboard

Monitoring

RAG

Pipeline, API, UI, review loop

OCR

Pipeline, API, UI, review loop

Workflow-first AI

Projects are framed around messy inputs, review states, user decisions, and handoff points.

End-to-end architecture

Coverage from ingestion and model calls to APIs, databases, dashboards, deployment, and monitoring.

Production-aware delivery

Case studies include trade-offs, failure modes, validation paths, and what should improve next.

Featured work

Case studies that show how the system is built, not just what it looks like.

Each project explains the problem, architecture, AI component, data flow, trade-offs, and what still needs real-world validation.

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LLM Automation / Knowledge Retrieval

RAG Customer Support System

Case Study

A support assistant concept that retrieves internal knowledge, drafts grounded answers, and keeps escalation visible for human agents.

Problem Solved

Support teams often lose time searching scattered SOPs, product docs, and previous tickets before answering recurring questions.

Next.jsFastAPILangChainQdrantPostgreSQLOpenAI API

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OCR / Document Processing

Finance OCR

Demo

A document extraction workflow for finance documents with review states, validation checks, and export-ready structured fields.

Problem Solved

Finance teams manually copy invoice, receipt, and statement data into spreadsheets or accounting systems.

PythonFastAPIPaddleOCRPostgreSQLNext.jsDocker

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LLM Workflow / Recruiting Automation

AI Screening CV

Private

A CV screening workflow that parses resumes, maps evidence to job criteria, and produces review-friendly candidate summaries.

Problem Solved

Recruiters and hiring teams spend too much time reading resumes without a consistent rubric.

Next.jsNode.jsPostgreSQLOpenAI APIEmbeddingsTailwind CSS

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Skill snapshot

A practical stack for AI products that need backend depth and usable interfaces.

The stack is organized around what a real AI system needs: model capability, data flow, application logic, infrastructure, and operator-facing UX.

AI / ML

LLMRAGOCRComputer VisionEmbeddingsVector SearchEvaluation

Backend

PythonFastAPINode.jsPostgreSQLMongoDBRedis

Frontend

Next.jsReactTypeScriptTailwind CSSDashboard UI

Infrastructure

DockerCI/CDCloudflareVPSMonitoring

AI Tooling

LangChainQdrantONNX RuntimePaddleOCROpenAI API

Proof of engineering thinking

What this portfolio is designed to prove

Can model a business workflow before choosing tools.

Can design RAG, OCR, and computer vision pipelines with review loops.

Can connect AI services to backend APIs, databases, and dashboards.

Can communicate technical trade-offs clearly to recruiters, CTOs, and clients.

Available for focused AI builds

Need an AI workflow that works outside a demo video?

I can help design the pipeline, backend, dashboard, and production checks needed to turn an AI idea into a maintainable system.

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