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Both TeepTrak and MachineMetrics are leading platforms for real-time machine monitoring and OEE improvement \u2014 but they are built for different manufacturing environments and solve different problems. If TeepTrak vs MachineMetrics<\/strong> is on your evaluation list, this comparison will help you identify which platform delivers more value for your specific operation. The honest answer: both are strong products, and the right choice depends heavily on what you make and how your shop floor is organized.<\/p>\n MachineMetrics<\/strong> is a US-based industrial IoT and machine analytics platform founded in Springfield, Massachusetts. It has built a strong reputation in North American manufacturing, particularly in precision machining, CNC shops and discrete parts manufacturing environments. MachineMetrics focuses on connecting CNC machines and other production equipment to deliver real-time utilization, OEE and performance data to machine operators and shop floor managers. The company is venture-backed and has developed deep integrations with Fanuc CNC controls (via FOCAS protocol) and other major machine tool brands.<\/p>\n TeepTrak<\/strong> is a French-founded OEE specialist established in 2014, deployed in 450+ factories across 30+ countries. Clients include Stellantis, Hutchinson, Alstom, Safran, Aptargroup and Kraft Heinz. TeepTrak is designed for broad industrial manufacturing environments \u2014 automotive assembly, food and beverage, pharmaceuticals, packaging, electronics \u2014 as well as precision machining. Its JEMBA AI engine differentiates it analytically, and its US team operates from Chicago with Kate Sherman as US Lead.<\/p>\n Both platforms deliver real-time OEE monitoring, downtime tracking and production dashboards. The divergence lies in three dimensions: sector focus, analytical depth and deployment flexibility.<\/p>\n MachineMetrics:<\/strong> Strongest in CNC machining, precision parts manufacturing and discrete manufacturing environments. Fanuc FOCAS integration is a genuine competitive advantage for shops running Fanuc-controlled machine tools. The platform is designed with machine shop operators and machinists in mind \u2014 the interface and metrics (spindle utilization, program run time, part count) reflect this focus.<\/p>\n TeepTrak:<\/strong> Designed for broad industrial manufacturing including automotive assembly lines (Stellantis, Hutchinson), food and beverage production (Kraft Heinz, Nutriset), pharmaceuticals, packaging (Aptargroup) and electronics. Also serves precision machining environments via non-intrusive sensors and PLC connectivity. The key difference: TeepTrak’s non-intrusive current and vibration sensors connect machines with no digital interface at all \u2014 legacy equipment with no CNC control, no PLC, no network connection. This matters in plants where a portion of the equipment is older or non-digital.<\/p>\n Verdict:<\/strong> For a pure CNC machining environment with Fanuc controls, MachineMetrics’ native FOCAS integration is a genuine advantage. For mixed manufacturing environments \u2014 assembly, process, packaging, food \u2014 TeepTrak’s broader sensor range and cross-industry depth wins.<\/p>\n MachineMetrics:<\/strong> Strong on real-time machine utilization analytics, program-level performance data and shift reporting. The platform has developed AI-assisted features for anomaly detection and utilization forecasting, leveraging its CNC machine data streams.<\/p>\n TeepTrak \u2014 JEMBA AI:<\/strong> JEMBA (Joint Equipment Management and Business Analytics) is an AI engine trained on real downtime data from 450+ factories across multiple industries and geographies. It goes beyond anomaly detection to automatically identify root cause patterns in downtime data \u2014 for example, correlating a specific operator shift with a specific downtime type, or identifying that a machine consistently fails after 6 hours of continuous runtime. JEMBA also generates predictive maintenance alerts before breakdowns occur. The breadth of training data across 450+ global deployments gives JEMBA a pattern recognition advantage that a single-sector platform cannot match.<\/p>\n Verdict:<\/strong> TeepTrak on depth and breadth of AI-driven root cause analysis. MachineMetrics on CNC-specific machine analytics.<\/p>\n MachineMetrics:<\/strong> Deployment typically takes days to weeks depending on machine connectivity complexity. Fanuc FOCAS connections are well-documented but still require configuration per machine.<\/p>\n TeepTrak:<\/strong> Standard deployment in 48 hours on a first production line without stopping production. Non-intrusive sensors install without machine modification. Field V4 tablets arrive pre-configured. Operator training takes 2 to 3 hours.<\/p>\n Verdict:<\/strong> TeepTrak on raw deployment speed.<\/p>\n MachineMetrics:<\/strong> Strong in North America. Expanding into the UK market. Multi-site capabilities available but the platform is more North American-centric in its customer base and support infrastructure.<\/p>\n TeepTrak:<\/strong> Deployed in 30+ countries with local teams in France (Paris), USA (Chicago) and China (Shenzhen). MoniTrak provides real-time cross-plant benchmarking for global industrial groups. Native multilingual support (EN\/FR\/DE\/ES\/ZH). Built for global manufacturing groups from day one.<\/p>\n Verdict:<\/strong> TeepTrak for global multi-plant manufacturers.<\/p>\n MachineMetrics:<\/strong> Excellent CNC machine connectivity. Support for non-CNC equipment (conveyors, presses, packaging lines) through additional sensors, but CNC is the core strength.<\/p>\n TeepTrak:<\/strong> Equally strong on CNC environments and non-CNC production equipment. Non-intrusive current and vibration sensors connect any machine regardless of age, brand or digital interface. This is the decisive advantage in mixed plants where CNC machines share the floor with mechanical presses, packaging lines, conveyors and manual assembly stations.<\/p>\n Verdict:<\/strong> TeepTrak for mixed manufacturing environments. Draw for pure CNC shops.<\/p>\n MachineMetrics is the stronger choice if you operate a dedicated CNC machining or precision parts manufacturing environment, primarily in North America, where Fanuc FOCAS native integration and spindle-level analytics are your primary requirement. If your shop runs predominantly Fanuc-controlled machine tools and you need deep program-level performance data per part, MachineMetrics delivers purpose-built value for that specific context.<\/p>\n TeepTrak is the stronger choice for mixed manufacturing environments \u2014 any plant where CNC machines share the floor with non-CNC production equipment. For global industrial groups that need consistent OEE benchmarking across plants in multiple countries. For manufacturers in automotive, food, pharmaceutical, packaging or electronics where cross-industry AI-trained analytics deliver more relevant insights. For any operation that needs live data in 48 hours rather than weeks.<\/p>\n Yes. TeepTrak supports Fanuc CNC connectivity via FOCAS protocol alongside its full range of PLC integrations (Siemens, Mitsubishi, Rockwell, Fanuc, and 30+ other brands). For shops with mixed Fanuc CNC and non-digital equipment, TeepTrak provides unified OEE monitoring across the entire plant floor.<\/p>\n MachineMetrics has been expanding into the UK market. Its primary customer base and support infrastructure remain concentrated in North America. TeepTrak is deployed in 30+ countries with dedicated local teams in the US, France and China.<\/p>\n TeepTrak can be deployed in parallel during a transition period to ensure data continuity. Historical MachineMetrics data can be imported where export formats support it. Deployment on a first line takes 48 hours without stopping production.<\/p>\n Both platforms incorporate AI-driven analytics. JEMBA \u2014 TeepTrak’s AI engine \u2014 is trained on downtime data from 450+ factories across multiple industries and geographies, enabling cross-industry pattern recognition that a single-sector platform cannot replicate. MachineMetrics’ AI is stronger on CNC-specific analytics (spindle utilization prediction, program-level anomaly detection).<\/p>\n MachineMetrics uses a SaaS subscription model, typically priced per machine or per site. TeepTrak similarly uses a SaaS subscription per production line with hardware (sensors and tablets) included or sold separately. Both platforms require contacting sales for specific pricing \u2014 neither publishes standard rate cards.<\/p>\n Compare TeepTrak on your own plant data \u2014 free 48h POC<\/a><\/p>\n See how TeepTrak performs across manufacturing environments. Visit our customer success stories<\/a> by industry.<\/p>\nWho They Are<\/h2>\n
Where They Compete and Where They Diverge<\/h2>\n
1. Sector and Equipment Focus<\/h3>\n
2. AI and Analytical Depth<\/h3>\n
3. Deployment Speed<\/h3>\n
4. Multi-Site and International Coverage<\/h3>\n
5. Equipment Connectivity Beyond CNC<\/h3>\n
Summary Scorecard<\/h2>\n
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\n \nCriteria<\/th>\n TeepTrak<\/th>\n MachineMetrics<\/th>\n<\/tr>\n<\/thead>\n \n CNC\/Fanuc native integration<\/td>\n \u2705 Supported<\/td>\n \u2705 Best-in-class<\/td>\n<\/tr>\n \n Non-CNC legacy equipment<\/td>\n \u2705 Non-intrusive sensors<\/td>\n \u26a0\ufe0f Limited<\/td>\n<\/tr>\n \n AI root cause analysis<\/td>\n \u2705 JEMBA (450+ plants)<\/td>\n \u26a0\ufe0f CNC-focused<\/td>\n<\/tr>\n \n 48h deployment<\/td>\n \u2705<\/td>\n \u26a0\ufe0f Days to weeks<\/td>\n<\/tr>\n \n Global multi-site (30+ countries)<\/td>\n \u2705<\/td>\n \u26a0\ufe0f US-centric<\/td>\n<\/tr>\n \n Food\/pharma\/automotive depth<\/td>\n \u2705 Stellantis, Kraft Heinz\u2026<\/td>\n \u26a0\ufe0f Machine shop focus<\/td>\n<\/tr>\n \n US local support<\/td>\n \u2705 Chicago team<\/td>\n \u2705 Springfield MA<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n When to Choose MachineMetrics<\/h2>\n
When to Choose TeepTrak<\/h2>\n
FAQ<\/h2>\n
Does TeepTrak support Fanuc CNC machines?<\/h3>\n
Is MachineMetrics available outside the United States?<\/h3>\n
Can TeepTrak replace MachineMetrics?<\/h3>\n
Which platform has better AI analytics?<\/h3>\n
What is MachineMetrics’ pricing model?<\/h3>\n