Serhii P.

🚀 𝗙𝗿𝗲𝗲 𝗔𝗜 𝗽𝗿𝗼𝗷𝗲𝗰𝘁 𝗮𝘀𝘀𝗲𝘀𝘀𝗺𝗲𝗻𝘁 𝘄𝗶𝘁𝗵𝗶𝗻 𝟐𝟒 𝗵𝗼𝘂𝗿𝘀: 𝗜’𝗹𝗹 𝗿𝗲𝘃𝗶𝗲𝘄 𝘆𝗼𝘂𝗿 𝗶𝗱𝗲𝗮, 𝗿𝗲𝗰𝗼𝗺𝗺𝗲𝗻𝗱 𝘁𝗵𝗲 𝗿𝗶𝗴𝗵𝘁 𝗔𝗜 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, 𝗮𝗻𝗱 𝗼𝘂𝘁𝗹𝗶𝗻𝗲 𝘁𝗵𝗲 𝗮𝗿𝗰𝗵𝗶𝘁𝗲𝗰𝘁𝘂𝗿𝗲 𝗮𝗻𝗱 𝗻𝗲𝘅𝘁 𝘀𝘁𝗲𝗽𝘀. I build production-ready AI systems: AI Agents, RAG applications, LLM integrations, and AI-powered SaaS using Python, FastAPI, LangGraph, and modern LLM APIs. I help startups and businesses turn AI ideas into working production systems, not just prototypes or ChatGPT wrappers. My core expertise is AI Agent Development, RAG Development, LLM Integration, AI Automation, and Python/FastAPI backend development. I can take an AI feature from architecture and data pipelines to agent workflows, API integrations, deployment, and production monitoring. 🏆 Production AI experience: ZALP: AI-powered food-delivery platform: AI agents, LSTM demand forecasting, PyTorch ETA prediction, courier routing, and automation for 1,500+ orders/day, with peaks of 5,000 orders/day and 95% on-time delivery. Vivat: high-load e-commerce: ML recommendation and personalization systems supporting an operation processing 20,000 orders/day, using Matrix Factorization and Neural Collaborative Filtering. SPORTO: AI-native SaaS: multi-agent AI architecture with 26 AI processes, LangChain/LangGraph, RAG, Qdrant, Garmin Connect API, personalized training generation, and safety validation. Team 404: technical consulting and AI/data solutions for a professional triathlon team. 🤖 AI Agents & Automation I build AI agents that can reason through multi-step workflows, use tools, access business data, call APIs, and execute actions. ✔️ AI Agent Development ✔️ LangChain / LangGraph ✔️ Multi-agent systems ✔️ Agentic workflows ✔️ Function calling & tool use ✔️ AI workflow automation ✔️ Structured outputs with Pydantic ✔️ Guardrails and validation ✔️ CRM / ERP / SaaS / REST API integrations 📚 RAG & Generative AI I develop production RAG applications and LLM-powered systems connected to private business data. ✔️ Retrieval-Augmented Generation (RAG) ✔️ Vector databases ✔️ Semantic search ✔️ Hybrid search ✔️ Document processing & ingestion ✔️ Embeddings & reranking ✔️ Knowledge assistants ✔️ PDF / document Q&A ✔️ LLM evaluation with Ragas / LangSmith ✔️ OpenAI / Claude API integration Typical RAG and AI chatbot applications include internal knowledge bases, customer support assistants, document search, semantic search, AI copilots, and AI-powered SaaS features. 🧠 AI / ML Engineering Beyond LLM applications, I build traditional Machine Learning and Deep Learning systems when they provide measurable business value. ✔️ Recommendation Systems: Matrix Factorization, ALS, SVD, NCF, LightFM, two-tower models, candidate generation and ranking ✔️ Forecasting: LSTM, GRU, Prophet, ARIMA/SARIMAX, XGBoost, LightGBM ✔️ Optimization: demand forecasting, inventory optimization, dynamic pricing, route optimization ✔️ Personalization: recommendation engines, ranking, lead scoring, churn prediction ✔️ NLP: BERT, DeBERTa, sentence-transformers, topic modeling, sentiment analysis ✔️ Computer Vision: YOLOv8/YOLO11, OpenCV, OCR ⚙️ Production AI & Backend I don't stop at the AI model. I build the infrastructure required to run AI applications in production. Python is my primary language. ✔️ Python / FastAPI ✔️ TypeScript ✔️ PostgreSQL / pgvector ✔️ Qdrant / Chroma / FAISS ✔️ Docker ✔️ GitHub Actions / CI/CD ✔️ MLflow / DVC ✔️ AWS / GCP ✔️ Model deployment & monitoring ✔️ LLM observability 💼 What I Can Build AI Agent Development: autonomous agents, multi-agent systems, tool calling, business process automation RAG Development: enterprise knowledge assistants, semantic search, document Q&A, private-data chatbots AI Chatbot Development: customer support, internal assistants, AI copilots, context-aware conversational systems LLM Integration: OpenAI, Claude, LLM APIs, structured outputs, function calling, existing SaaS/API integration AI SaaS Development: AI-powered MVPs and production SaaS platforms with Python/FastAPI backends Recommendation Systems: personalization, candidate generation, ranking, recommendation engines Forecasting & Optimization: demand forecasting, ETA prediction, routing, inventory and operational optimization Why Clients Hire Me ✔️ Production experience: AI systems handling thousands of daily transactions ✔️ End-to-end ownership: architecture → data → AI → API → deployment → monitoring ✔️ Business-focused AI: I build AI to solve measurable business problems ✔️ Strong AI engineering: Python, FastAPI, LangChain, LangGraph, RAG, ML and MLOps ✔️ Clean architecture: maintainable systems designed to grow ✔️ Clear communication: practical explanations without unnecessary jargon ✔️ Existing-system integration: I can add AI to your current SaaS, API, CRM, ERP, or backend I'll help you define the right AI architecture, MVP scope, technology stack, and implementation approach.