Automation

Overview I design and deploy practical AI solutions that automate real business workflows - not generic chatbots, but purpose-built systems connecting your internal data, compliance rules, and operational processes with large language models. From hooking Claude or GPT into your application to building multi-agent orchestration pipelines, I handle the integration layer so AI works naturally within your existing systems. What I Can Do For You LLM and API Integrations Model integration: Connect Claude, GPT, Gemini, or local open-source models to your application via REST APIs or SDKs Context management: Conversation history, session management, and context window optimization Structured output: Parse LLM responses into typed, validated data your application can consume reliably Fallback chains: Graceful degradation across multiple model providers for high availability Retrieval-Augmented Generation (RAG) Knowledge base QA: Question-answering over your company documentation, policies, product catalogs, and technical manuals Vector search: Embedding pipelines with vector databases for semantic search over large document collections Real-world example: TOFY Go! - custom RAG pipelines for TOEFL-specific educational content delivery at Bee2 AI Agentic Systems Multi-agent orchestration: Hierarchies of specialized AI agents - one retrieves data, another analyzes, another formats output Sub-agent delegation: Complex tasks broken into parallel sub-tasks handled by independent AI agents Human-in-the-loop: Critical decisions routed to human approvers before execution Business Process Automation Document processing: Auto-extract, classify, and route invoices, contracts, and forms Reporting automation: AI-generated daily/weekly reports from structured and unstructured data Workflow triggers: Event-driven automation (new order, AI checks inventory, generates response) MCP (Model Context Protocol) Servers Custom MCP servers: Expose your internal tools, databases, and APIs as MCP tools for AI assistants Development tools: Custom MCP servers for code analysis, deployment automation, and DevOps Technologies LLMs: Claude API, OpenAI API, Gemini, open-source models (Llama, Mistral, Qwen) Frameworks: LangChain, custom agent orchestration Data: RAG pipelines, vector databases (Pinecone, Qdrant), structured SQL Protocol: Model Context Protocol (MCP) Integration: REST APIs, webhooks, message queues Deployment: Docker, AWS Lambda, serverless Languages: TypeScript, Python

Overview I build desktop applications that bridge gaps between web platforms, internal systems, and business operations. Using Electron.js for cross-platform desktop apps, I create unified interfaces that automate workflows, synchronize data across systems, and replace manual processes - proven with SonTechBot, an enterprise automation platform connecting Trendyol Fast Market, ERP systems, and license management. What I Can Do For You Desktop Application Development Cross-platform apps with Electron.js: One codebase running on Windows, macOS, and Linux with native OS integration Native capabilities: File system access, system tray, notifications, offline storage, and hardware access Auto-update: Seamless update delivery so your users always run the latest version Enterprise Automation E-commerce automation: Connect marketplaces (Trendyol, Hepsiburada, Amazon) with your ERP and inventory systems ERP integration: Real-time bidirectional sync between web platforms and on-premise database systems Order processing automation: Auto-download, validate, and process orders from multiple channels into a single dashboard Business Process Tools Unified dashboards: Single interface to monitor orders, inventory, financial summaries, and operational metrics License management: Software license tracking, activation, and renewal systems Reporting tools: Automated report generation and distribution Architecture Marketplace APIs to Desktop App to ERP System (MSSQL) to Company Website and License Management ...

Overview I build custom platforms and SaaS products - end-to-end systems with user management, real-time data processing, and automated reporting. From multi-tenant restaurant menu systems (QR Menu SaaS) to automated investment analysis platforms (Musli) with cron-based data collection and daily reporting, I take your idea from concept to deployed product. What I Can Do For You Full-Stack SaaS Products Multi-tenant architecture: Database-per-tenant or shared schemas with row-level isolation Authentication and authorization: JWT, OAuth 2.0, role-based access control (RBAC), session management Subscription management: Stripe/Paddle integration, plan tiers, usage tracking, invoicing Admin dashboards: Tenant management, usage analytics, billing overview, user administration Custom Platforms Data platforms: Automated data collection, processing, analysis, and reporting pipelines API-first design: RESTful or GraphQL APIs designed for consumption by multiple clients (web, mobile, third-party) Static publishing: Generate and deploy static site versions of dynamic data - ideal for customer-facing content from admin interfaces Automated Systems Scheduled data pipelines: Cron-based or event-driven data collection, processing, and report generation Investment/financial tools: Automated portfolio analysis, risk metrics (Sharpe, Sortino, MaxDD), technical indicators (RSI, MACD, Bollinger) Notification systems: Email, Telegram, or messaging platform delivery for reports and alerts How I Build Architecture and stack selection: Monolith first, microservices when necessary Rapid prototyping: Get a working product in your hands fast Production hardening: CI/CD, monitoring, backups, disaster recovery Iterate: Continuous delivery of features based on real usage Technologies Backend: Go (sqlx), TypeScript (NestJS, Express), Python Frontend: React Native (Expo - iOS, Android, Web), React/Next.js Databases: PostgreSQL, MSSQL, SQLite, DynamoDB Infrastructure: AWS, Docker, CI/CD Automation: Cron-based pipelines, schedulers, event-driven triggers Payments: Stripe, Paddle