Logify for BCT – AI-Powered Log File Analysis

Starting point

Support staff at a B2B software company spent hours to days manually analyzing unstructured log files to identify error sources. No systematic pattern recognition, no automatic prioritization — every case was handled manually.

Solution

Development of an AI system that automatically analyzes large, unstructured log files, detects errors and anomalies, and generates prioritized solution suggestions with context. Built in 48 hours at the Black Forest Innovation Hackathon, then deployed to production at the client site.

Technology stack

• Python (Backend / Analysis Engine)
• OpenAI LLMs (Error and Anomaly Detection)
• ChromaDB (RAG Indexing and Retrieval)
• Pydantic (Data Validation / Structured Output)
• TypeScript, ReactJS (Frontend / Support Interface)

Result & Impact

• IT support response time reduced from days to seconds
• Winner at the Black Forest Innovation Hackathon
• On-premise deployment at client site completed April 2026
• Follow-up project (HubSpot Support Copilot) in concept phase