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sattva2020/README.md

Hi, I'm Ruslan πŸ‘‹

AI engineer building production AI products: LLM agents, RAG with measured quality, MCP tools.
I take a product from data model to deployed, monitored service, and I make AI output reliable:
validated, testable, traceable to source data.

Before software I spent 10+ years running production infrastructure (Linux, Windows Server, Azure,
telecom billing, networks). So the systems I build are deployed, secured and monitored, not just written.

πŸ“ Ukraine Β· remote Β· griban.dev Β· LinkedIn


πŸš€ Products in production

HealBot.pro β€” AI front-desk assistant for private clinics. Talks to patients in Telegram, Viber, WhatsApp, Messenger, Instagram and a website chat, collects complaints,
routes each patient to the right specialist and books the appointment. Docker, automated deploys, payments, bot protection. (private repository)

Cryonic CRM β€” AI-first CRM for outbound sales. Next.js + NestJS, self-hosted Supabase (PostgreSQL + pgvector), background AI jobs and call transcription (Whisper) in a Redis queue, subscription billing, versioned public API. (private repository)

🧠 Open source

Project What it is
memlab Project memory for coding agents: graph-aware code retrieval + decision memory, MCP server, pre-registered benchmarks against other tools. Python.
dokploy-mcp MCP server exposing the full Dokploy API through 4 gateway tools (~1% of context) or 500+ generated tools, with safety annotations. TypeScript.
myhealth-mcp Self-hosted, FHIR-native MCP server for citizen-controlled health data in the EU.
agents-md-in-the-wild 480 real agent instruction files (AGENTS.md, CLAUDE.md…) from 272 top repositories, refreshed weekly, with patterns measured. Python.
talersme AI assistant that helps European SMEs integrate GNU Taler payments.
N8N-AI-Starter-Kit-Advanced Production n8n + AI services deployment: monitoring, CI/CD, disaster recovery.

πŸ›  What I work with

AI: Claude & OpenAI APIs, agents & tool calling, MCP, RAG, embeddings, pgvector, evals, structured outputs
Backend: Python (FastAPI, Pydantic), TypeScript (Node.js, NestJS), PostgreSQL, Supabase, Redis, queues
Frontend: Next.js, React
Ops: Docker, nginx, Dokploy, Railway, CI/CD, Prometheus, Grafana, Sentry, Linux, Azure
Automation: n8n, Make, Zapier

πŸ’¬ Work with me

Open to freelance and contract work: AI assistants and chatbots, RAG over documents, agent systems, AI features in SaaS products. I communicate in writing (English, Ukrainian, Russian).

Pinned Loading

  1. dokploy-mcp dokploy-mcp Public

    MCP server for Dokploy β€” full API access through 4 gateway tools (~1% context) or 500+ generated tools, with safety annotations

    TypeScript 1 1

  2. agents-md-in-the-wild agents-md-in-the-wild Public

    Python

  3. memlab memlab Public

    Project memory for coding agents: code + decision retrieval over a symbol graph, MCP server, graph views, and a pre-registered evaluation vs AMG and graphify

    Python

  4. myhealth-mcp myhealth-mcp Public

    Open-source Model Context Protocol (MCP) server for citizen-controlled health data in the EU. Self-hosted, FHIR-native, privacy-by-architecture. NLnet NGI Zero Commons Fund #13 (2026).

    Dockerfile

  5. N8N-AI-Starter-Kit-Advanced N8N-AI-Starter-Kit-Advanced Public

    Production-ready N8N deployment with AI services, advanced monitoring, CI/CD pipelines, and disaster recovery capabilities

    Shell

  6. talersme talersme Public

    AI assistant that removes the integration barrier preventing European SMEs from adopting GNU Taler payments. NLnet NGI TALER call #13 (2026).