Log Intelligence for Android Device Manufacturers
Diagnose crashes, ANRs, kernel panics, and HAL failures across your entire device portfolio — in minutes, not days.
What We Analyze
Upload logs from phones, tablets, wearables, and custom Android devices
Full system diagnostics including logcat, dumpsys, kernel logs, and system properties from any Android device
Application and framework event logs captured via ADB, MDM, or on-device logging tools
Device tree issues, driver probe failures, thermal zone events, memory pressure, and kernel panics
System service state dumps — battery stats, wifi, display, activity manager, and 30+ subsystems
How to Collect Your Logs
Standard Android tools — no custom instrumentation required
ADB Bugreport
- 1.Connect USB or WiFi ADB to device
- 2.Run adb bugreport
- 3.Upload the generated .zip file
ADB Logcat
- 1.Run adb logcat -d for a snapshot
- 2.Or adb logcat -f for continuous capture
- 3.Upload the .txt log file
MDM Collection
- 1.Configure Knox, Esper, SOTI, or custom MDM
- 2.Schedule bugreport collection remotely
- 3.Bulk upload collected logs
Kernel Logs
- 1.Run adb shell dmesg on device
- 2.Or extract from bugreport zip
- 3.Upload for BSP and driver analysis
logcat.ai supports bugreport .zip files up to 100MB+, plain text logcat, and raw dmesg output. No proprietary tools required.
Why Device Debugging Is Hard
Android devices span more layers than any other consumer product
Expertise bottleneck
Only a handful of senior engineers can debug cross-layer issues spanning app, framework, kernel, and hardware. Everyone else waits.
Manual triage takes days
50MB+ bugreports contain millions of log lines. Correlating events across logcat, dmesg, and dumpsys is manual, slow, and error-prone.
Field returns are expensive
Undiagnosed issues lead to delayed OTAs, warranty claims, and customer churn. Every day without root cause costs money.
Issues span 6+ subsystems
A camera crash might originate in the HAL, propagate through a kernel driver, involve a device tree misconfiguration, and manifest as a framework ANR. No single tool connects these layers.
Built for Device Engineers
AI-powered tools designed for the unique challenges of Android device debugging
10-Subsystem Parallel Analysis
Automatically analyzes Applications, System Services, Memory, Power, Network, Storage, Security, CPU, and more — in parallel. Results in under 5 minutes.
Deep Research
An autonomous AI agent that investigates complex issues step by step. Searches patterns, correlates stack traces, looks up CVEs, and builds comprehensive root cause reports.
Delta Comparison
Compare bugreports across firmware versions, device variants, or time periods. Isolate regressions and identify exactly what changed between builds.
Learn more about DeltaCross-Layer Correlation
Traces issues from app crashes through framework services, system server, HAL, and kernel — identifying the true root cause across the full Android stack.
Autonomous Investigation for Device Issues
Deep Research traces issues across the full Android stack automatically
Cross-Layer Device Investigation
Multi-step analysis across application, framework, and kernel layers
Cross-layer correlation complete
Track Regressions with Delta
Upload bugreports from different firmware versions or device variants. Delta identifies new crashes, changed behavior, and regressions that appeared between builds.
Delta Correlation Engine
Multi-file cross-layer analysis
Who Uses This
Engineers across the Android device development lifecycle
Pre-Release QA
Catch system_server crashes, fingerprint failures, and framework issues in pre-release testing — not from customer bugreports.
Field Failure Diagnosis
Upload MDM-collected bugreports from field devices. Get root cause analysis without shipping the device back to the lab.
Firmware Regression Tracking
Use Delta to compare bugreports across firmware versions. Find exactly which build introduced the regression and what changed.
Frequently Asked Questions
Common questions about device manufacturer log analysis
logcat.ai supports Android bugreport .zip files, plain text logcat output (all formats: threadtime, brief, time), raw dmesg output, and dumpsys text dumps. We handle files from any Android version 8.0+.
We routinely process bugreports over 100MB containing millions of log lines. The AI analysis typically completes in under 5 minutes regardless of file size.
Yes. Delta accepts multiple bugreports and compares them side by side — identifying new crashes, changed behavior, performance regressions, and driver failures that appeared between firmware versions.
Deep Research is an autonomous AI agent that investigates issues step by step. It parses logs, identifies anomalies, correlates events across subsystems, searches for known issues and CVEs, and builds a comprehensive root cause report with citations — typically in 5-10 minutes.
We support Linux kernel logs (dmesg) from any embedded Linux device. For full bugreport analysis, the device needs to run Android (AOSP or custom builds). We also support embedded Linux distributions like Yocto, Buildroot, and OpenWrt for kernel-level analysis.
All data is encrypted in transit (TLS 1.3) and at rest (AES-256). Your log data is never used to train AI models. SOC2 Type II certification is in progress. Enterprise plans include SSO/OIDC and custom data retention policies.
There's no setup required. Upload a bugreport or logcat file through the web interface and get analysis results in minutes. For enterprise deployments, we offer dedicated cloud instances with SSO/OIDC, custom retention, and API access.
See it in action
Request a demo to see how logcat.ai can transform your debugging workflow.