Case StudyPrivate implementation details removed. Prototype — not claimed as a shipped production product.
NLP Report Generation Prototype
An internal AI hackathon prototype that generates reports from natural-language queries with intelligent follow-up handling; selected among finalists.
Role: Builder — prompt engineering, OpenAI API integration, follow-up handling.Duration: 2025
OpenAI APIPrompt EngineeringLLMNLPPrototype
Context
Operational reporting often depends on rigid forms. Natural-language queries can make exploration faster for internal users.
Problem
Generating useful reports required predefined forms instead of conversational follow-up.
Ownership
- Natural-language report generation flow
- Intelligent follow-up handling
- Prompt engineering and OpenAI API integration
Architecture
User query → prompt orchestration → OpenAI completion → structured report response → optional follow-up turns.
flowchart LR User[User Query] --> Orchestrator[Prompt Orchestration] Orchestrator --> LLM[OpenAI API] LLM --> Report[Report Response] Report --> FollowUp[Follow-up Handling]
Key Technical Decisions
| Decision | Why | Trade-off | Result |
|---|---|---|---|
| Prototype-first hackathon approach | Validate conversational reporting quickly | Not production-hardened | Selected among finalists and considered for exploration |
Implementation
- Implemented natural-language query handling
- Added intelligent follow-up turns
- Applied prompt engineering for report structure
Results
- Selected among internal hackathon finalists
- Considered for product exploration
Reflection
- Finalist status is not the same as a production launch — keep that distinction clear.