AI bid/no-bid analyst on Telegram — open to try
Send a government procurement document (KAK/RKS, PDF or Word) to the bot and a four-agent pipeline replies in about a minute: a compliance matrix against a company profile, red flags cited to specific articles of Perpres 16/2018 via RAG over a per-article embedding index, a bid/no-bid score, and a deterministically assembled Excel workbook plus a six-chapter draft proposal in Word. Every deploy is gated by CI: 23 regression checks on real documents — including one that verifies no cited article is fabricated — must pass 100% first.
Regulation-cited red flags (RAG) · 23-check eval gate on Cloud Build · Excel + .docx artifacts
Built with Google ADK, Gemini, Vertex AI embeddings, Cloud Run, Cloud Build, Telegram Bot API
Tender Scout — Procurement Intelligence Agent
Proprietary code
Agentic web app over live Indonesian e-procurement data
A tool-calling agent that searches and screens live tenders from SPSE/SIRUP public data, scores qualification gaps against a company profile, runs semantic search, and exports results to Excel. Built to be auditable end to end: every figure in a report traces back to a logged HTTP request, and per-agent token metering reports the real cost of a session in USD and rupiah.
Live SPSE/SIRUP data · Auditable request log · Per-agent cost metering (USD–IDR)
Built with Google ADK, Gemini, Cloud Run, FastAPI
Enterprise Multi-Agent AI System
Proprietary code
Metrodata Electronics, enterprise client
A production multi-agent system automating risk management, prescriptive maintenance, and conversational analytics over enterprise data. Includes a three-layer Medallion pipeline on BigQuery, deployed to Cloud Run in the Jakarta region.
3 specialized agents · L0→L2 data pipeline · 6+ file types ingested
Built with Google ADK, Gemini, Vertex AI, BigQuery, Cloud Run, FastAPI, Docker
SDLC Orchestrator for Gemini Enterprise
Proprietary code
Metrodata (MII) contribution to a Google Gemini Enterprise initiative
An ADK agent live inside Gemini Enterprise that lets non-technical users (HR, finance) turn a plain-language idea into SDLC artifacts: a PRD for Confluence, epics and user stories for Jira, and a working application repo with CI — codegen guaranteed to build, with Spring Boot backends passing mvnw verify and React + Vite frontends passing npm run build. To keep token costs sane, 60 bundled engineering skills load on demand: the prompt carries only a compact menu, cutting per-message context from ~100k to ~4k tokens.
Live in Gemini Enterprise · ~25× smaller context via on-demand skills · Build-verified codegen (Java & React)
Built with Google ADK, Gemini, Vertex AI Agent Engine, Gemini Enterprise, Jira & Confluence APIs, Spring Boot, React
Thesis; paper accepted at ICoICT 2026 (IEEE-Scopus)
A human-in-the-loop automation framework that extracts 11 structured fields from invoice images with OCR and writes them straight into Excel through robotic process automation, cutting a manual data-entry task to a fraction of the time.
11 fields extracted · Real-time Excel via RPA · 25× faster than manual
Built with Python, Tesseract OCR, OpenCV, Pandas, xlwings
Exploratory extension of the thesis · unpublished
A follow-up study benchmarking transformer NER models for the same invoice-extraction task: fine-tuning BERT and LayoutLMv3 on an annotated invoice set and comparing three OCR engines for the upstream text layer.
97.25% F1 LayoutLMv3 · 96.35% F1 BERT · 11 target fields
Built with PyTorch, LayoutLMv3, BERT, Hugging Face, Tesseract
AI Sales Agent
Conversational commerce on OpenClaw and Gemini
A conversational sales assistant for e-commerce sellers, built on the OpenClaw agent framework with an MCP server and WhatsApp integration. Gemini handles smart product tagging with automated classification across 6 attribute types.
6 auto-tagged attributes · WhatsApp channel · MCP tool protocol
Built with OpenClaw, Gemini API, TypeScript, MCP, Node.js
