Sold by: NeenOpal
NeenOpal's AI-powered industrial diagnostics accelerator deploys in under 60 minutes on AWS, reducing downtime and boosting OEE with Amazon Q and IoT SiteWise.
Overview
Industrial operations often face extended downtime and reduced productivity due to inefficient troubleshooting and diagnosis. NeenOpal's Assisted Diagnosis and Troubleshooting solution leverages Amazon Q, AWS IoT SiteWise, Amazon Bedrock, and other AWS services to help operators and engineers quickly identify root causes, access real-time equipment insights, and receive AI-driven recommendations.
By integrating with ERP, MES, and CMMS systems, the solution provides a unified workflow that accelerates issue resolution, optimizes OEE (Overall Equipment Effectiveness), and reduces operational costs. What makes this solution unique is our pre-built accelerator - a turnkey solution that can be deployed in your AWS environment in under 60 minutes. From there, it can be fine-tuned to align with your business goals, specific data sources, and operational workflows.
Key Features
- AI-powered diagnostic assistant: Real-time troubleshooting guidance using Amazon Q and Amazon Bedrock.
- Natural language interface: Query systems conversationally for faster insight retrieval.
- Sensor and OT data integration: AWS IoT SiteWise integration for equipment health monitoring.
- Knowledge retrieval with RAG: Access SOPs, manuals, and maintenance logs for contextual answers.
- Automated work order creation: AI recommendations trigger corrective actions within ERP/CMMS systems.
- Seamless workflow integration: Works across SCADA, MES, ERP, and ticketing platforms.
Benefits
- Reduced downtime: Faster root cause detection minimizes operational disruptions.
- Improved OEE: AI-optimized diagnostics maximize equipment uptime.
- Operational visibility: Real-time health and performance insights across production lines.
- Data-driven maintenance: Preventive strategies powered by IoT sensor data.
- Optimized workforce efficiency: Empower operators to resolve issues without deep technical expertise.
- Rapid time-to-value: Get started with a fully functional PoC in under 60 minutes.
Security and Data Handling
The solution deploys entirely within your own AWS account, ensuring your operational data never leaves your environment. Data at rest and in transit is encrypted using AWS-native encryption services. Access controls leverage AWS IAM policies, and the solution is FTR (Foundational Technical Review) validated by AWS, confirming adherence to AWS security best practices.
Use Cases
- Predictive Maintenance for Manufacturing: Anticipate and prevent breakdowns on production equipment such as CNC machines, compressors, and conveyor systems using AI analysis of IoT sensor data streams.
- Production Line Troubleshooting: Quickly resolve bottlenecks and equipment failures in automotive assembly, food and beverage packaging, or pharmaceutical batch processing environments.
- Knowledge Augmentation for Technicians: Provide maintenance teams with AI-curated guidance drawn from historical resolutions, SOPs, and equipment manuals.
- Automated Workflow Orchestration: Streamline ticketing, work orders, and corrective actions across integrated ERP and CMMS platforms.
Prerequisites and Scope
- An active AWS account with permissions to deploy CloudFormation stacks.
- AWS IoT SiteWise configured for target equipment (or NeenOpal can assist with setup).
- Access to relevant documentation (SOPs, maintenance logs, equipment manuals) for RAG indexing.
- The pre-built accelerator supports standard industrial protocols and is designed for initial deployments covering production lines with IoT-connected assets.
How It Works
- Operators interact with the AI assistant using natural language.
- The system queries IoT sensor data, maintenance logs, and SOPs using RAG.
- AI delivers real-time recommendations for diagnosis and corrective actions.
- Insights can trigger automated work orders and integrate with ERP/CMMS systems.
Getting Started
- Discovery: Engage NeenOpal to scope user roles, equipment, and workflows.
- Deploy: Launch the pre-built accelerator in under 60 minutes in your AWS environment.
- Validate: Run a Proof of Concept by connecting IoT sensor data, maintenance logs, and SOPs.
- Scale: Fine-tune and expand for production-ready troubleshooting and predictive maintenance.
To begin, contact us at aws_marketplace@neenopal.com to schedule a discovery call and plan your 60-minute PoC deployment.
Highlights
- Deploy a turnkey AI-powered diagnostic PoC in under 60 minutes within your own AWS environment. The pre-built accelerator leverages Amazon Q, AWS IoT SiteWise, and Amazon Bedrock to deliver real-time troubleshooting guidance through a natural language interface. Your operational data stays in your AWS account with native encryption and IAM-based access controls.
- Reduce unplanned downtime and improve OEE by enabling operators to identify root causes faster using AI-driven insights from IoT sensor data, maintenance logs, and SOPs. The RAG-powered system retrieves contextual answers from your existing documentation, empowering frontline teams to resolve issues without deep technical expertise.
- Automate work orders and corrective actions by integrating with ERP, MES, CMMS, and SCADA systems. The solution supports standard industrial protocols and connects across your operational technology stack to streamline workflows, eliminate manual ticket creation, and accelerate mean-time-to-repair across production lines.
Details
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NeenOpal Inc. is an AWS Advanced Tier Services Differentiated Partner with Data and Analytics and SaaS Competencies, multiple AWS Service Deliveries, and FTR-validated solutions.
Engagement Structure
A typical engagement follows four phases:
- Discovery (Week 1): A scoping workshop to define user roles, target equipment, data sources, and integration requirements. Deliverable: scoping document and architecture plan.
- Deployment (Week 1-2): Launch the pre-built accelerator in your AWS environment in under 60 minutes. Deliverable: configured accelerator with initial data connections.
- Proof of Concept (Weeks 2-3): Connect IoT sensor data, maintenance logs, and SOPs to validate diagnostic accuracy. Deliverable: PoC results report.
- Fine-Tuning and Handoff (Weeks 3-4): Optimize for production readiness. Deliverables: runbook, architecture diagram, and operational documentation.
Buyer Responsibilities
- Provide access to an AWS account with CloudFormation deployment permissions.
- Assign an OT engineer or plant-level SME for equipment and workflow context.
- Supply relevant SOPs, maintenance logs, and equipment manuals for RAG indexing.
- Designate an IT administrator for IAM and network configuration support.
Support Contact
For professional support, engagement inquiries, or assistance with your deployment, contact us at aws_marketplace@neenopal.com . Visit <www.neenopal.com > for additional information about our services and capabilities.