Engineering AI Agents In Action

The Challenge

Engineering teams running multiple simulation scenarios face a bottleneck: manually comparing outputs, validating assumptions, and identifying which results need expert attention is slow and inconsistent.

The Solution

A visual workflow where specialist agents load simulation outputs, compare scenarios in parallel, evaluate uncertainty ranges, check physical constraints, and produce a ranked recommendation with traceable reasoning.

Key Agents

• Scenario Loader — Ingests simulation output files
• Comparison Agent — Identifies differences & anomalies
• Constraint Validator — Checks physical assumptions
• Recommendation Writer — Generates traceable engineering report

The Challenge

Complex engineering decisions in oil & gas require deep technical knowledge and commercial judgment simultaneously. A single AI agent cannot cover both domains with the depth and traceability required.

The Solution

An orchestrator agent routes queries to specialist sub-agents — a Petroleum Engineering Expert and a Commercial Analyst — treating each as a callable tool and combining their outputs into a structured, explainable recommendation.

Key Agents

• Orchestrator — Decomposes query, routes to specialists
• Technical Expert — Petroleum engineering reasoning
• Commercial Analyst — Economic & risk analysis
• Synthesis Agent — Merges outputs with full run log