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Real-time debate platform (WebRTC, iOS, Android, AI) and P2P grocery marketplace (Next.js, NestJS, Stripe, maps). End-to-end full-stack delivery.

grig-teo.space

In development

A monorepo that powers my public site and a complete personal health pipeline. A SwiftUI app reads my COLMI R10 ring over a reverse-engineered BLE protocol with no vendor cloud, and streams heart rate, SpO2, stress, HRV, sleep stages and activity into a NestJS/Postgres backend. That backend turns the data into hourly AI tips, a recovery score, streaks, weekly digests and an AI doctor, which queries any metric over any date range, reads scanned lab results and examines note photos through a local vision model. It ships as a Next.js site (en/ru/ro) with an admin dashboard, an iOS app with a widget and HealthKit gap-fill, a macOS tip app with notifications, and a Telegraf bot, all self-hosted on a single VPS.

Highlights

  • — Reverse-engineered the COLMI R10 BLE protocol in Swift: heart rate, SpO2, stress, HRV, sleep stages and activity sync straight to my server, with no vendor cloud
  • — Built an AI doctor (Kimi K3) with tool access to the whole health database: any metric over any date range, sleep stages, activities, notes and document scans, including images
  • — Generated hourly AI health tips from live metrics, weather correlations and journal notes, using DeepSeek with an on-VPS Ollama fallback
  • — Built the sleep pipeline: stage parsing, composite scoring, a recovery score against 14-day HRV and resting-HR baselines, and deviation alerts
  • — Ran four surfaces on one backend: a Next.js 15 site (en/ru/ro) with an admin dashboard, a SwiftUI iOS app with a widget, a macOS tip app and a Telegraf bot with photo and video notes
  • — Self-hosted the entire stack on a single VPS with no third-party cloud: Postgres, MinIO with public and private buckets, an Ollama vision model, Docker and nginx

TypeScript · Next.js 15 · NestJS · SwiftUI · CoreBluetooth · HealthKit · Telegraf · PostgreSQL · TypeORM · MinIO · Docker · nginx · Kimi K3 · DeepSeek · Ollama

Touchstone

In development

AI coding agents are good at writing code but cannot tap through a real app on a real phone. Touchstone closes that gap: an agent orders a test over a REST API or MCP, human testers pick it up on real devices and return structured reports with video and screenshot evidence uploaded through presigned S3 URLs. The platform includes a full economy: budgets, multi-currency accounts with CBR FX conversion, a tester ledger, withdrawals and payouts via Alfa and Stripe. It also has a trust and safety layer with an evidence-analysis worker, report corroboration, tester streaks and honeypot tasks that catch farming.

Highlights

  • — Exposed a pure REST API for agents (X-API-Key) and an MCP server with order_test/get_report, so agents order human tests like any other tool call
  • — Modelled the task lifecycle as a state machine with slot matching, a review flow and versioned report schemas (report/v1 JSON)
  • — Built the evidence pipeline: presigned S3 uploads of screen recordings and screenshots, analysed by a separate worker
  • — Added trust and safety with report corroboration across testers, streak scoring and honeypot tasks that catch fraud
  • — Built the full payment flow: top-ups through Alfa and Stripe, multi-currency accounts with CBR rates applied at approval, a ledger for testers, withdrawals and payouts
  • — Backed Next.js dashboards with i18n using FastAPI, PostgreSQL and Alembic, a Redis worker and MinIO, deployed with Docker Compose and nginx on my VPS

Python · FastAPI · Next.js 14 · React 18 · PostgreSQL · Alembic · Redis · MinIO/S3 · MCP · Stripe · Docker · nginx

Projects | WebRTC, Mobile & Marketplace Apps