# Prover Reviews
**Vendor:** Proven Information Technologies  
**Category:** [Other Automotive Software](https://www.g2.com/categories/other-automotive)
## About Prover
ProVER is a system solution enabling anomaly detection for test engineers monitoring ECUs and their networks for complex vehicles/platforms. Modern vehicles/platforms contain big data and intensive software, and vehicles/platforms under test comprise networks of many ECU (Electronic Control Units) data. ProVER utilizes state-of-the-art data techniques to analyze traces both offline-by importing data from Automotive sectors well-known data logger file formats (or private cloud data) and live data feed from networks and various protocols (i.e. CAN, LIN, FlexRay, Ethernet, UART). Usage and Benefits ProVER, enables software intensive-high data networked automotive/platform developers’ test engineers to analyze and diagnose anomalies more efficiently either at laboratories or at the field by monitoring time-stamped and correlated ECU messages. Reduces Test Engineering efforts and enables easy analysis and detection of anomalies. Enables on-field testing and diagnostic analysis. Enables focusing on anomalies instead of analyzing terabytes’ of data logs. Analysis of anomalies by the correlated data. Monitoring trends of anomalies by graphic user interfaces for prognostic analysis. Features Script Editor for Test Engineers to insert rules Live monitoring of bi-directional flow of ECU data Graphical User Interface to visualize the source of anomalies Live analysis of performance indicators in the form of graphics Visualization for Routing Tables Automatic anomaly detection Integration to existing data recording systems For more information, you can visit our site (www.proven.com.tr), or drop us an email(info@proven.com.tr).






- [View Prover pricing details and edition comparison](https://www.g2.com/products/prover/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-16+11%3A06%3A53+-0500&secure%5Bsession_id%5D=54c871ac-dc67-419a-8478-11d700dd590e&secure%5Btoken%5D=993bcd2c54a3c123243cd4a486d13c8076370b33a73cb1a9f6a889506629b0de&format=llm_user)


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