LLM-Assisted Incident Summarization & Clustering
Jan 2026 – PresentBuilt an end-to-end incident intelligence pipeline that ingests large-scale system/application logs, generates structured incident summaries with LLMs, embeds summaries, and clusters incidents to identify duplicates and recurring failure patterns. Includes a backend service and lightweight UI/API to explore incidents and clusters.
PythonLLMsEmbeddingsClusteringNLPREST API
Highlights
- —Built an end-to-end incident intelligence pipeline: ingest large-scale system/application logs, generate structured incident summaries with LLMs, embed summaries, and cluster incidents to identify duplicates and recurring failure patterns
- —Implemented a backend service and lightweight UI/API to explore incidents and clusters, making practical accuracy vs cost/latency tradeoffs to support scalable operation on noisy real-world logs
Results
- —Scalable pipeline handling noisy real-world logs with practical accuracy vs cost/latency tradeoffs