Enterprise AI Analysis
LLM Agents for Interactive Workflow Provenance: Reference Architecture and Evaluation Methodology
Modern scientific discovery increasingly relies on complex workflows across the Edge, Cloud, and HPC continuum. This analysis presents an evaluation methodology and reference architecture for LLM-powered agents that enable natural language querying of workflow provenance data, enhancing reproducibility and insight generation.
Key Outcomes & Tangible Impact
Our LLM-powered provenance agent dramatically improves data accessibility and analysis efficiency, translating directly into significant gains for scientific discovery.
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Accuracy with GPT-4
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Avg. Response Time
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Queries Answered Accurately
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Reduced Context Overflows
Deep Analysis & Enterprise Applications
Select a topic to dive deeper, then explore the specific findings from the research, rebuilt as interactive, enterprise-focused modules.
Methodology
Evaluation
Applications
Workflow Provenance Query Characteristics
When
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Who
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Query Scope
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Query Workload Type
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Data Type
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Provenance Type
The core methodology introduces a systematic approach to evaluating LLM agent performance in workflow provenance interaction, emphasizing RAG pipeline design and prompt engineering across diverse query classes.
GPT-4 Performance Highlight
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Accuracy in Full Context
GPT-4 achieved near-perfect scores (97%) with full context, demonstrating strong performance across diverse query classes, as evaluated by an LLM-as-a-judge approach. This highlights the effectiveness of comprehensive context in enhancing model accuracy.
| LLM Model | OLTP Score (Avg) | OLAP Score (Avg) |
|---|---|---|
| GPT-4 | 0.97 | 0.95 |
| Claude Opus 4 | 0.94 | 0.92 |
| LLaMA 3-70B | 0.85 | 0.78 |
| Gemini 2.5 Flash Lite | 0.75 | 0.65 |
| LLaMA 3-8B | 0.60 | 0.50 |
Case Study: Live Interaction with Computational Chemistry Workflow
The LLM-powered agent successfully analyzed a real-world chemistry workflow on a supercomputer, answering complex queries about bond dissociation enthalpies, atom counts, and chemical properties with high accuracy. This demonstrates the agent's ability to bridge the gap between users and complex provenance data in live scientific discovery.
- Dynamic Dataflow Schema: Automatically inferred and updated, enabling LLM to effectively respond to runtime queries without direct database access.
- Natural Language Querying: Users interacted via natural language, receiving tabular results, plots, and summaries.
- Performance & Generalization: Agent demonstrated strong reasoning capabilities and generalized from a synthetic workflow to a complex chemistry workflow without domain-specific tuning.
- Context Management: Lightweight, metadata-driven approach prevents context window overflows, crucial for large HPC workflows.
Calculate Your Potential ROI
Estimate the efficiency gains and cost savings your enterprise could achieve by integrating LLM-powered agents into your workflow management.
Estimated Annual Savings
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Hours Reclaimed Annually
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Your AI Journey: A Clear Roadmap
We guide enterprises through a structured implementation, ensuring a smooth transition and maximum impact for LLM-powered provenance.
Phase 1: Discovery & Strategy
Deep dive into your existing workflow provenance, data structures, and scientific objectives to define clear AI agent goals.
Phase 2: Architecture & Customization
Design the modular provenance agent architecture, integrating with your ECH continuum and tailoring RAG pipelines for domain-specific context.
Phase 3: Implementation & Integration
Deploy the agent, instrument workflows for provenance capture, and integrate with existing LLM services and data storage solutions.
Phase 4: Evaluation & Refinement
Utilize the evaluation methodology to assess agent performance, fine-tune prompts, and iteratively improve accuracy and user interaction.
Phase 5: Scaling & Operationalization
Scale the solution across your enterprise, providing ongoing support and enabling continuous scientific discovery with intelligent provenance.
Ready to Transform Your Scientific Workflows?
Unlock interactive data analysis and accelerate discovery with our LLM-powered provenance agents. Schedule a free consultation to see how we can tailor a solution for your enterprise.
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