Company Overview
The client is a global leader in high-performance RF and microwave signal processing and conditioning, serving defense, energy, and federal sectors where precision and reliability are non-negotiable. Their complex multi-level Bill of Materials (BOMs) span thousands of components requiring meticulous engineering processes and deep institutional knowledge.
Engineering and operations teams relied on manual processes to analyze BOMs, answer "what-if" scenarios, and make sourcing decisions. Questions like "What happens if Supplier X delays Component Y?" required hours of manual investigation across spreadsheets and multiple systems.
Executive Summary
JBS Dev built an AI-enabled agentic platform for a global RF/microwave manufacturer, replacing weeks of manual BOM analysis with natural language queries, multi-agent intelligence, and real-time cross-functional visibility—all layered on existing ERP infrastructure without operational disruption.
info The data existed across multiple systems, but extracting actionable insights demanded significant engineering time and expertise.
Business Challenge
Manufacturing data trapped across disconnected systems, forcing engineers to spend hours manually analyzing BOMs and inventory instead of solving strategic problems.
Engineering Efficiency:
- Hours spent manually analyzing data instead of engineering work
- Repetitive queries for the same operational questions
- Limited ability to explore complex "what-if" scenarios
- Dependency on senior engineers for institutional knowledge
Operational Responsiveness:
- Slow identification of supply chain risks and impacts
- Delayed responses to parts shortages or supplier issues
- Manual coordination across engineering and sourcing
- Limited visibility into downstream effects of changes
Knowledge Management:
- Institutional knowledge trapped in senior engineers' heads
- New engineers required months to build context
- No systematic way to capture engineering tradecraft
- Tribal knowledge created single points of failure
System Integration:
- Aging ERP with no intuitive query interface
- No cross-functional visibility across BOMs and inventory
- Technical expertise required to extract basic reports
- Data silos prevented holistic analysis
JBS Dev's Approach
Rather than replace the existing ERP system, JBS Dev built an AI-enabled agentic platform layered on top of the company's existing data infrastructure. The solution uses Azure AI Services, Django REST Framework, and React to provide a conversational interface where engineers ask simple questions and receive instant, accurate analysis.
The platform delivers three core capabilities:
1. Natural Language BOM Querying
Ask complex questions in plain English—no SQL or technical expertise required
2. Multi-Agent Intelligence with Institutional Memory
Specialized AI agents orchestrate workflows, apply business rules, and learn from expert feedback
3. Real-Time Cross-Functional Visibility
Unified view across BOMs, inventory, orders, and sourcing, exportable to Excel or PDF
Engineers can now ask questions like "Which work orders are affected by a delay in Component X from Supplier Y?" and receive immediate answers with supporting data, alternative recommendations, and impact analysis. The platform is scalable, domain-aware, and built to preserve engineering tradecraft while accelerating operational decision-making.
Multi-agent AI platform built on existing ERP infrastructure without disruption
Business Outcomes
Before: Manual Analysis
After: AI-Powered Platform
verified_user Human-in-the-Loop AI for Mission-Critical Decisions: Engineers validate AI outputs, correct errors, and teach the system, ensuring accuracy while preserving institutional control over critical manufacturing decisions.
What Made This Work
Multi-Agent Architecture for Complex Engineering Logic
Specialized AI agents handle BOM analysis, inventory forecasting, and supplier relationships. Agent orchestration manages complex workflows that no single AI model could handle alone.
Built on Existing Infrastructure Without Disruption
The AI platform integrates seamlessly with the legacy ERP system via APIs and data connectors. Manufacturing operations continued uninterrupted during deployment.
Domain-Aware AI Tuned for Manufacturing Context
JBS Dev tuned the AI with client-specific terminology, business rules, and engineering tradecraft, ensuring responses aligned with operational reality rather than generic LLM outputs.
Human-in-the-Loop for Trust and Accuracy
Engineers validate AI recommendations, correct errors, and teach the system. This feedback loop preserves institutional control while allowing the AI to learn and improve over time.
Conversational Memory for Context-Aware Interactions
The platform remembers previous questions, user preferences, and project context across sessions. Engineers don't repeat themselves—conversations flow naturally, accelerating analysis.