Post by Dhruv Thakkar

Hey network, During my co-ops in hardware validation, applications, and characterization teams, I repeatedly saw the same problem across different engineering workflows. Engineers spend a huge amount of time manually analyzing logs, oscilloscope screenshots, measurement data, and lab outputs, then converting that information into structured reports and debugging decisions. Whether it was validation reporting, benchmarking analysis, or datasheet-related work, a lot of the process was repetitive and highly manual. As systems become more complex, this workflow becomes slower, harder to scale, and heavily dependent on individual engineers. I’m building a system to automate that workflow. The platform takes raw hardware test data including logs, CSVs, and scope screenshots and automatically: 1. Extracts measurements✅ 2. Detects anomalies✅ 3. Identifies possible root causes✅ 4. Suggests next debugging steps✅ 5. Generates structured validation summaries and reports✅ The goal is to help hardware teams move faster from raw data to engineering decisions while reducing repetitive manual analysis work. Currently building the MVP💻 and looking for engineers interested in testing it with real validation data and providing feedback. Please feel free to reach out! #HardwareEngineering #ElectricalEngineering #EmbeddedSystems #HardwareValidation #Semiconductors #AI #MachineLearning #EngineeringTools #ProductEngineering #SignalIntegrity #PCBDesign #PowerElectronics #ChipDesign #HardwareTesting #EngineeringAutomation #DeveloperTools #Startups #YC #B2BSoftware #TechInnovation #velocity