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AI Diagnostic and Feedback Pipeline
Day1 Company · Oct 2025 - Jan 2026
Spring AIGeminiAmazon BedrockOpenAISpring Boot
Tasks
- •Redesigned a diagnosis process that depended on direct HTTP calls and one synchronous prompt into a 7-step Spring AI pipeline: STT load, semantic chunking, STT correction, metric calculation, LLM feedback, question generation, and notification
- •Reduced CS tickets by 98% through better diagnostic quality
- •Integrated the pipeline into the existing Java/Spring environment to reduce maintenance burden and development complexity
- •Separated pipeline stages asynchronously to reduce bottlenecks and stabilize processing time
- •Assigned Gemini, Amazon Bedrock, and OpenAI models to stage-specific roles and designed a back-office flow for changing models and prompts without downtime
- •Reduced LLM cost by about 50%
- •Added hallucination correction and retry logic for format validation failures
- •Reduced diagnostic report generation time from 6-7 minutes to 1-2 minutes