G2

Tanish P.

Manager

Enterprise (> 1000 emp.)

10/14/2026

"Real-Time Machine Health Insights with Confident, Actionable Diagnostics"

4.5/5

What do you like best about Augury?

The continuous IoT sensor monitoring and AI-driven prescriptive diagnostics have transformed how our team manages reliability. Instead of relying on manual vibration routes or guessing based on time intervals, Augury’s real-time alerts pinpoint exact machine faults such as early bearing wear, shaft misalignment, or imbalance weeks before a failure occurs. UI/UX: The clean dashboard organizes asset health by criticality, allowing us to review vibration, magnetic flux, and thermal trends at a glance without getting bogged down in raw data. Integrations & Workflow: Augury integrates directly with our CMMS/EAM, automatically triggering work orders with detailed root-cause diagnoses. The automated alerts and expert-backed remediation steps save our planners and technicians hours of troubleshooting every week. AI & Support: The "human-in-the-loop" model where certified vibration analysts validate AI alerts gives our team 100% confidence to act without chasing false alarms. Pricing & ROI: We saw an immediate payback within months by catching a major motor defect during a scheduled outage, preventing tens of thousands of dollars in emergency downtime and overtime labor. Unexpected Benefit: Beyond preventing downtime, monitoring machine efficiency helped us identify energy leaks and baseline abnormalities, lowering our utility consumption on heavy rotating equipment. Performance and speed of execution is very good too. Review collected by and hosted on G2.com.

What do you dislike about Augury?

While Augury provides powerful machine health capabilities, there are notable limitations and friction points that can impact day-to-day operations: UI / UX: The web dashboard and reporting interfaces can occasionally feel rigid. When managing a large facility, navigating through custom filters or filtering down a high volume of data takes extra clicks, and initial adoption requires a bit of a learning curve for new maintenance users. Integrations & Workflow: While work order generation is possible, the "alert-to-action" gap remains a bottleneck if alerts aren't triaged quickly. When integrations with certain CMMS/EAM setups require custom mapping, automated handoffs can stall, leaving maintenance planners to manually bridge the gap. Performance & Hardware: Because Augury relies heavily on its proprietary hardware ecosystem ("hardware lock-in"), you cannot easily map or ingest data from pre-existing third-party sensors you might already have installed on secondary assets. Additionally, high-frequency sampling modes can strain battery life or connectivity on remote machines. Pricing & ROI: The platform requires a meaningful upfront and ongoing financial commitment through its per-asset subscription model. For smaller plants or tight operational budgets, scaling coverage across secondary and non-critical assets is cost-prohibitive, forcing hard compromises on what gets monitored. Support & Onboarding: The initial deployment process is resource-intensive. Mapping out asset hierarchies, establishing baselines, and getting plant personnel fully aligned requires heavy cross-functional coordination before you realize steady-state value. AI & Intelligence: The proprietary AI acts somewhat like a "black box." When an automated diagnostic or human-in-the-loop validation conflicts with a local technician's gut instinct on the floor, it can cause friction or distrust if the underlying diagnostic path isn't completely transparent. Review collected by and hosted on G2.com.

What problems is Augury solving and how is that benefiting you?

We struggled with reactive firefighting and calendar-based routine maintenance that frequently missed developing machine faults, but now we can leverage continuous AI diagnostics to catch exact mechanical failures weeks in advance. This has resulted in a significant drop in emergency downtime, fewer wasted labor hours on false alarms, and streamlined resource planning. Before implementing Augury, our maintenance team operated in a reactive cycle: We relied on manual vibration routes performed every few weeks or waited for loud noises, high temperatures, and catastrophic equipment failure on the factory floor. Sudden machine breakdowns forced emergency shutdowns, requiring expensive expedited parts shipping, frantic troubleshooting, and costly overtime labor to get production back online. Rigid threshold alerts triggered frequent false positives, causing technician fatigue and building a skepticism that made teams hesitant to act early. After adopting Augury’s continuous IoT monitoring and AI-driven prescriptive diagnostics, the workflow shifted completely: Instead of guessing asset health or working blindly between fixed service windows, we receive clear, validated alerts pinpointing specific faults like early bearing wear, imbalance, or misalignment well before a failure occurs. Maintenance planners now have weeks of lead time to order parts proactively and schedule repairs during planned operational windows rather than interrupting production mid-shift. Quantifiably, catching these defects early has driven measurable impact: Cost & Downtime Reduction: By intercepting major equipment issues during scheduled maintenance windows rather than suffering sudden breakdowns, we have cut emergency repair expenses and eliminated hundreds of hours of unplanned downtime. Payback & ROI: The platform paid for itself in less than six months by preventing a single major motor and compressor failure that otherwise would have cost over $100,000 in lost output and heavy emergency labor. Review collected by and hosted on G2.com.