About
Factory AI (F7i.ai) is an industrial AI platform that combines predictive maintenance (PdM) and a Computerized Maintenance Management System (CMMS) into a single, unified solution. Designed for mid-sized manufacturers, it is fully sensor-agnostic—meaning it works with any existing sensors, PLCs, historians, or SCADA systems, eliminating the need for proprietary hardware. The platform deploys in brownfield plants in under 14 days using a no-code setup, requiring no data science expertise. The Predict module uses advanced machine learning to detect equipment anomalies before they escalate into critical failures, covering assets like pumps, fans, conveyors, and more. Real-time monitoring, visual dashboards, and targeted notifications help reliability engineers and maintenance coordinators shift from reactive firefighting to planned, confident interventions. The Prevent CMMS module—bundled at no additional cost—streamlines work order creation, asset management, and maintenance scheduling with AI-powered automation. Customers have reported a 25% reduction in maintenance costs and a 70% reduction in breakdowns. One food manufacturing client attributed approximately $500,000 in avoided downtime to the platform over 12 months. Factory AI is ideal for reliability engineers, maintenance coordinators, and operations leaders looking to modernize their maintenance strategy without overhauling existing infrastructure.
Key Features
- Sensor-Agnostic Anomaly Detection: Works with any existing sensors, historians, PLCs, or SCADA systems—no proprietary hardware required—to detect equipment anomalies using advanced machine learning before they cause failures.
- Bundled AI-Powered CMMS: Includes the Prevent CMMS module at no extra cost, enabling AI-driven work order generation, asset management, and maintenance scheduling in one unified platform.
- Rapid Brownfield Deployment: No-code setup allows manufacturers to deploy in under 14 days in existing (brownfield) facilities without requiring a data science team or major infrastructure changes.
- In-Depth Asset Monitoring: Provides granular performance insights for pumps, fans, conveyors, and other equipment with real-time notifications for issues requiring immediate attention.
- Predictive Alerts & Reporting: Delivers actionable predictive alerts that allow maintenance teams to plan interventions, secure spare parts, and avoid unplanned downtime before failures occur.
Use Cases
- A food manufacturing plant deploys Factory AI to monitor conveyor and pump health across two high-throughput sites, receiving predictive alerts that allow the team to plan maintenance interventions and avoid $500,000 in unplanned downtime over 12 months.
- A reliability engineer at a mid-sized industrial facility uses Factory AI's anomaly detection dashboards to identify developing faults in rotating equipment weeks before failure, shifting the team from reactive to proactive maintenance.
- A maintenance coordinator streamlines work order creation and scheduling using Factory AI's AI-powered CMMS, reducing paperwork and ensuring the right technician is dispatched with the right parts at the right time.
- A manufacturing operations leader deploys Factory AI across multiple brownfield plants in under two weeks, integrating with existing SCADA systems to gain centralized visibility into asset health without replacing existing infrastructure.
- A small maintenance team uses Factory AI's free CMMS plan to digitize asset records, track work orders, and build a maintenance knowledge base, preparing the organization for a future rollout of predictive maintenance capabilities.
Pros
- Works With Existing Infrastructure: Sensor-agnostic design means manufacturers don't need to replace hardware or overhaul their current SCADA or historian setups—dramatically lowering implementation barriers.
- Fast Time-to-Value: Deployment in under 14 days with a no-code setup means maintenance teams see results quickly without lengthy IT projects or data science dependencies.
- All-in-One PdM + CMMS: Combining predictive maintenance and a full CMMS in one platform eliminates the need for multiple disconnected tools and simplifies operations.
- Proven Cost Savings: Customers report a 25% reduction in maintenance costs and a 70% reduction in breakdowns, with documented cases of hundreds of thousands of dollars in avoided downtime.
Cons
- Industry-Specific Use Case: The platform is purpose-built for manufacturing and industrial environments, limiting its applicability for organizations outside of asset-heavy industries.
- Requires Existing Sensor Infrastructure: While sensor-agnostic, the platform still assumes some level of existing sensor deployment; organizations with no monitoring infrastructure will need hardware before benefiting fully.
- Paid Tier Needed for Larger Teams: The free plan is designed for small teams, and scaling to larger operations requires the $35/user/month business plan, which may add up for large workforces.
Frequently Asked Questions
Does Factory AI require proprietary sensors or hardware?
No. Factory AI is fully sensor-agnostic and works with your existing sensors, historians, PLCs, and SCADA systems. No proprietary hardware purchase is required.
How long does it take to deploy Factory AI?
The platform is designed for brownfield deployments and can be set up in under 14 days using a no-code configuration process—no data science team needed.
What is included in the free plan?
Factory AI offers a free plan for small teams that includes access to the Prevent CMMS. The Business plan at $35/user/month (billed annually) unlocks the full predictive maintenance Predict platform.
What types of equipment can Factory AI monitor?
The platform supports monitoring of a wide range of industrial assets including pumps, fans, conveyors, and other rotating or process equipment commonly found in manufacturing facilities.
What results can manufacturers expect from using Factory AI?
Based on customer results, manufacturers typically see a 70% reduction in equipment breakdowns and a 25% reduction in maintenance costs. One food manufacturing client attributed approximately $500,000 in avoided downtime to the platform over 12 months.
