AÖAhmet Özelinahmetozel.hashnode.dev·Jul 21 · 34 min readThe Anatomy of Production-Grade RetrievalRetrieval-Augmented Generation is often summarized as a three-step workflow: split documents, embed the chunks, and send the nearest results to a language model. That description is useful for a proto00
AÖAhmet Özelinahmetozel.hashnode.dev·Jul 16 · 40 min readBuilding a Local-First OCR + LLM Pipeline for Structured Business DocumentsTurning a scanned business document into reliable structured data is not a single-model problem. Optical character recognition is only one stage in a longer system that must handle image quality, page00
AÖAhmet Özelinahmetozel.hashnode.dev·Jun 8 · 2 min readOne MCP server for Jira, Confluence and Bitbucket: 61 tools under one configIf you want an AI agent to work with Atlassian, you quickly hit a practical annoyance: Jira, Confluence and Bitbucket are three products, and the usual answer is three separate MCP servers with three 00
AÖAhmet Özelinahmetozel.hashnode.dev·Jun 8 · 3 min readBuilding an agentic Jira automation platform with MCP and TemporalMost AI automation demos fall apart the moment a workflow needs to run longer than a single request. An agent makes a few tool calls, the process crashes or times out, and you lose all state. I wanted00
AÖAhmet Özelinahmetozel.hashnode.dev·Jun 8 · 3 min readDesigning a config-driven agentic RAG platform for customer supportCustomer support is one of the few places where RAG and agents earn their keep immediately: the questions are real, the knowledge changes constantly, and a wrong answer has a cost. I built an open-sou00
