GridGPT
A domain-specific AI assistant designed to make technical grid or energy information easier to query, summarize, and explore using natural-language interactions and grounded context.
Project Summary
- Status
- Planned
- Timeline
- Portfolio roadmap
- Visual proof
- Question -> Retrieval -> Grounded Answer
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Featured case-study visual
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Problem
Energy and grid datasets can be difficult to explore because information is distributed across tables, reports, and technical documentation.
Approach
Create a natural-language interface that retrieves relevant context, assembles source-grounded evidence, and returns answers with visible supporting sources.
Architecture
System flow and processing stages.
Stage 1
User question
Stage 2
Query processing
Stage 3
Retriever or dataset lookup
Stage 4
Context builder
Stage 5
LLM response generator
Stage 6
Source-grounded answer
Stage 7
User-facing interface
Data Sources
- TODO: Add actual grid or energy datasets
- TODO: Add technical reports or documentation sources
- Structured CSV/JSON files if applicable
Methods
- Retrieval-augmented generation
- Prompt design
- Source grounding
- Data preprocessing
Technologies
- Python
- FastAPI
- React or Next.js
- LLM API
- Vector search placeholder
Evidence and Screenshots
Visual assets to replace placeholders.
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GridGPT query interface
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Retrieved context/source panel
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Example query gallery
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Results
- Defined an AI system architecture for domain-specific data exploration.
- Planned a source-grounded answer workflow to avoid unsupported chatbot responses.
- Identified UI and evaluation artifacts needed to make the demo credible.
Metrics and Evaluation Needed
- Number of indexed sources
- Example query coverage
- Answer grounding checklist
- Latency if live demo is built
Challenges
- Avoiding unsupported AI claims.
- Grounding responses in real data and cited context.
- Evaluating answer quality for domain-specific questions.
Lessons Learned
- AI systems are more credible when retrieval and sources are visible.
- Domain-specific assistants need evaluation examples, not just a chat box.
- The interface should expose evidence, not hide it.
Future Work
- Add a guided query demo.
- Add source citation panels.
- Build a small evaluation set of expected answers and sources.
Interactive Demo Ideas
- Guided query demo with precomputed responses
- Citation/source viewer
- Example prompt gallery
What This Demonstrates