ASKING ANG
EDGE NODE PRIVATE PLATFORM {ok} {id} {sig} RAW · INTERCEPTED a9#fK2%… xQz= hmac…verify PARSED · STRUCTURED { "ok": true, "sig":"verified" } REVERSE ENGINEERING $ uvicorn api:app ✓ 200 · 38ms $ API LIVE PRODUCTION 200 ok DEPLOYBUILD PASSED GET /v1/feed · 401 → 200 sig = HMAC·reconstructed p50 · 42 ms

ASKING ANG — INDEPENDENT BACKEND ENGINEER · PRIVATE API REVERSE ENGINEERING

I turn platforms without public APIs into production-ready endpoints.

I reverse-engineer private APIs and application protocols, rebuild them as stable backend services, then integrate and deploy them into real products.

PRIVATE PLATFORM REVERSE ENGINEERING API APPLICATION PRODUCTION
12 34 56 NETWORK · CAPTURE GET /v1/feed POST /auth POST /v1/pay · sig GET /v1/user $ replay --resign ok
02THE ENGINEER

I work where the public API ends.

The work starts before the code. I capture real traffic, inspect every request, and map authentication, signatures and obfuscation until the protocol underneath stops being a mystery.

Then — and only then — I write the backend that makes it boring: stable services, honest docs, monitoring, and deployments that stay up while everyone else is still reading error pages.

CAPTURE → ANALYZE → RECONSTRUCT → SHIP

03CASE 01 · EXAPI

One backend. Eight private platforms. Zero public docs.

EXAPI unifies eight independent platforms behind a single private-API gateway — reverse-engineered clients, queued workers, Redis caching and a monitored pipeline, serving live production traffic.

8PLATFORMS UNIFIED
<100msMEDIAN RESPONSE
12,847,203PRODUCTION REQUESTS · LIVE
CHAT FEED DASHBOARD MEDIA MOBILE + 3 MORE 8 PLATFORMS · NO PUBLIC API API GATEWAY QUEUE REDIS DATABASE MONITORING p50 · 82ms EXAPI CORE · REQUEST PIPELINE AUTH REPLAYS · SIGNATURE FORGE · RATE LIMITS · RETRIES ADMIN CONSOLE CLIENT APP PARTNER API · WEBHOOK ✓ 200
SMULEVAULT · TRACK 0417 02:41 bitrate 256k · cache: redis · sig: verified NOW RECORDING PUBLISH → VAULT DB clips · meta MEDIA BACKEND clip_0417.m4ameta · ok · cached {media}
04CASE 02 · SMULEVAULT

Media engineering for a platform that never shipped an API.

SmuleVault started with a waveform and a locked door. I reconstructed the platform's private media endpoints, built the retrieval backend, and turned raw audio streams into structured, cacheable responses — clips, metadata, and covers served with sub-second latency.

The hard part was never the audio. It was the handshake in front of it.

WAVEFORM → PROTOCOL → JSON → VAULT

05CASE 03 · AGRICULTURAL MARKET INTELLIGENCE

From marketplace listings to a national price API.

Scrapers collect agricultural listings across regions; a normalization pipeline cleans, deduplicates and geocodes them; analytics turn market noise into price curves, supply signals and a queryable dataset.

MARKETPLACE FEED · LIVE RICE · 50 KG ฿1,420 CASSAVA · 1 T ฿8,150 MAIZE · 100 KG ฿5,860 EXTRACTNORMALIZEENRICH PRICE INDEX · 12 MO SUPPLY MAP DATASET → API /v1/prices
AUTODESK · BOT AUTO · 84ms message… PROTOCOL LAYER PAYLOAD msg · plaintext SIGN / ENCODE FRAMED PACKET 0x7F A3 ··· 0x9C TLS · TRANSPORT BOT SERVICE RULE ENGINE if msg ~ /price/ if msg ~ /order/ → route · reply · log MESSAGEPROTOCOL BOTAUTOMATION
06CASE 04 · LINE AUTOMATION

A bot that speaks the protocol, not just the API.

An automation layer for a messaging platform: incoming messages are parsed at protocol level — framed, signed, decoded — then routed through a rule engine and LLM helpers, and answered in milliseconds.

Full conversations handled end to end, with no human in the loop and no official bot API in sight.

MESSAGE → PROTOCOL → BOT → AUTOMATION

07CASE 05 · AI INTEGRATION & DEPLOYMENT

AI inside real software — not in a demo notebook.

I don't just wire up a model API. I design the backend around it — prompt pipelines, context stores, streaming endpoints, cost and rate controls — then deploy it into existing products, from a single chat widget to a fully automated workflow.

EXISTING WEBSITE VPS · DOCKER ● BUILDING… ● PRODUCTION BACKEND · API MODEL GATEWAY add AI replies to checkout context: product-db · max_tokens: 512 POST /v1/ai/reply → stream: true rate-limited · cost-tracked · logged + EXISTING WEBSITEBACKEND AI / LLMPRODUCTION
SOURCE A SOURCE B RAW INCLEAN NORMALIZATION DATABASE API · /v1/records
08CASE 06 · SCRAPING & PIPELINES

A digital factory for clean data.

Collect → normalize → store → serve. Malformed pages in, structured records out: resilient scrapers, schema enforcement, incremental updates — and APIs on top of datasets that stay fresh without anyone babysitting them.

The web is an undocumented database. I build the extraction layer it's missing.

WEB → SCRAPER → NORMALIZATION → DATABASE → API

assemble → request → render → deploy MOBILE ● BUILDING… ● ONLINE
09CASE 07 · WEB DEVELOPMENT

The front door to everything above.

Dashboards, landing pages and admin tools that sit on top of the backends I build — assembled, deployed and kept alive. A supporting craft, done properly.

10SERVICES

What I take on.

POST /v1/pay sig=a9#f… ✓ rebuilt
S / 01

Private API Reverse Engineering

Unknown request → analyzed → reconstructed. Auth, signatures, obfuscation — mapped, documented, reproducible.

ENDPOINTS 200 ok38 ms versioned ·monitored
S / 02

API Development & Maintenance

Requests enter, responses leave — for years. Versioning, rate limits, monitoring, uptime worth trusting.

WEBSITE BACKEND AI / LLM request → model → production
S / 03

AI Integration & Deployment

From a prompt in a notebook to a model serving real traffic — inside software people already use.

RAW WEB PAGES CLEAN
S / 04

Web Scraping & Data Pipelines

Raw web data in, clean structured data out — pipelines that keep datasets fresh on schedule.

COMPONENTS → FUNCTIONING SITE
S / 05

Web Development

Interfaces for the systems I build — assembled, deployed, and very much alive.

11ENGINEERING PROCESS

The lifecycle, drawn to scale.

FULL LIFECYCLE · T+0 → T+∞ CAPTURE real traffic ANALYZE auth · signatures RECONSTRUCT protocol client INTEGRATE into the product DEPLOY vps · containers MAINTAIN monitor · evolve PROJECTASKING ANG — LIFECYCLE SHEET11 · REV C SCALE1 : 1
A GLOWING SIGNAL PASSES EACH STAGE — THE DRAWING ACTIVATES AS IT GOES. REV C · CHECKED · APPROVED
12TECH STACK

The constellation.

Every technology orbits a real backend architecture. Hover — or tap — one, and its part of the system lights up.

BOT GW GATEWAY WEB UI CAPTURE CACHE REDIS SERVICES QUEUE CONTAINERS POSTGRES DATASTORE AI SERVICE
BACKEND PythonFastAPIWorkers
API RESTWebhooks
REVERSE ENG mitmproxyhttpxfrida
FRONTEND JavaScriptHTML/CSS
INFRA DockerNginxLinux VPS
DATA PostgreSQLRedisPandas
AI LLM APIsRAGPrompt Eng

HOVER OR TAP A TECHNOLOGY — THE RELATED PART OF THE ARCHITECTURE LIGHTS UP

13CONTACT

New project.

API SKETCH NEW PROJECT STATUS · AWAITING BRIEF PROJECT RECEIVED STATUS · ONLINE — NETWORK ACTIVE ~/briefs $ tail -f inbox.log VPS
  • Private API Reverse EngineeringCORE
  • API Engineering & MaintenanceBUILD
  • Automation / Bot (LINE, WhatsApp)BOT
  • AI Integration & DeploymentAI
  • Web Scraping & Data PipelineDATA
  • Web DevelopmentWEB
  • Other ProjectCUSTOM

I read every brief myself and reply with a technical take, not a sales pitch — usually within a day. Prefer email directly? [email protected]

PRIVATE PLATFORM REVERSE ENG API WEB BOT AI PROD PRODUCTION

Have a platform without a public API?

Tell me what you're trying to access, automate, integrate, or build. I'll look at the technical problem first.