Singapore-based AI engineer | AI platforms | evaluation systems

Wes Lee

Builds backend-first AI platforms, multimodal evaluation systems, and operator-facing decision tools.

Currently AI Engineer and ASEAN Education Program Director at Elice. This site focuses on inspectable systems and selected private-code case studies across retrieval, evaluation, finance, forecasting, and decision support.

  • AI platforms
  • Evaluation systems
  • Retrieval and orchestration
  • Operator-facing products
Selected systems Portfolio intelligence
Selected flagship systems across finance, retrieval, evaluation, and document intelligence
Selected flagship systems Case studies across foundation models, retrieval, evaluation, and operator-facing products.
1,000+ technical docs queried in local RAG workflows
114K+ comments processed in NLP pipelines
70% analyst time reduced through workflow automation

Flagship case studies

Start with four flagship case studies that best represent the portfolio.

This set is intentionally small: the clearest signal for platform architecture, evaluation rigor, and operator-facing product execution.

Creator AI Platform visual

Edtech / AI platform

Creator AI Platform

A backend-first orchestration platform for learning-asset generation with staged discovery, retrieval, validation, and human review built into the product itself.

  • Workflow orchestration and quality gates
  • Discovery, retrieval, generation, and review stages
  • Private codebase with public case study
Intelligent Content Analyzer visual

Document intelligence / service architecture

Intelligent Content Analyzer

A modular document intelligence platform that splits upload, retrieval, generation, and evaluation into services rather than one monolithic demo app.

  • Hybrid retrieval and confidence checks
  • FastAPI gateway plus dedicated services
  • Multilingual workflow support
SlideBench AI Evaluation Workbench visual

Evaluation systems / multimodal

SlideBench AI Evaluation Workbench

A multimodal evaluation workbench for AI-generated slides and learning artifacts, combining deterministic metrics, retrieval, provenance checks, and judge-assisted scoring.

  • Deterministic metrics plus retrieval-assisted evaluation
  • Provenance checks and judge-assisted scoring
  • Private codebase with public case study
AI Portfolio Advisory System visual

Finance / foundation models

AI Portfolio Advisory System

A robo-advisor platform that applies TabPFN to investor risk assessment and pairs it with objective-aware portfolio optimization.

  • TabPFN risk profiling
  • Dynamic portfolio objectives
  • Interactive demo available

The supporting layer then broadens into workforce intelligence, prompt optimization, enterprise RAG, policy forecasting, inventory planning, graph ML, climate analytics, and other applied systems.

Current work

Current work centers on orchestration, evaluation, and operator review.

AI platforms

Backend-first systems that connect retrieval, generation, validation, and human-in-the-loop review.

Evaluation and observability

Benchmarking, evidence checks, regression coverage, tracing, and structured scoring for model behavior.

Product interfaces

FastAPI, Streamlit, and internal-tool patterns that give operators usable surfaces instead of opaque models.

Decision domains

Education, workforce intelligence, finance, public health, and business analytics where systems need to drive action.

Recent writing

Writing behind the systems.

Technical notes on implementation choices, evaluation logic, and what changed between experiment and usable product.

Next move

Need an engineer who can connect model quality with product execution?

Best fit is backend-first AI platforms, evaluation-heavy systems, and decision-support products moving beyond prototype stage.