The Investigation Engine at the Heart of logcat.ai
Deep Research doesn't search your logs — it investigates them. Multi-step, cross-layer, hypothesis-driven root-cause analysis that replaces hours of manual debugging.
Investigation, Not Search
Search tells you where a keyword appears. Deep Research tells you why your system failed. It reads your logs, forms hypotheses, runs targeted investigations across every system layer, and builds a root-cause report with evidence — the same process a senior engineer follows, in minutes instead of hours.
- Plans an investigation strategy based on your question, then executes multiple search steps autonomously
- Forms and tests hypotheses — if the first lead is a dead end, it pivots to the next
- Traces causal chains across kernel, framework, drivers, and app layers
- Produces a structured report: root cause, evidence from log lines, and actionable recommendations
Why Manual Debugging Breaks Down
The issues that matter most are the ones grep can't solve.
You Can't Grep for Unknown Unknowns
Real root causes often involve events you didn't think to search for. A thermal shutdown triggered by a GPU driver bug won't appear in a search for 'crash'.
Cross-Layer Correlation Is Manual
The kernel panic is in dmesg. The triggering ANR is in logcat. The memory pressure is in dumpsys. Connecting them requires jumping between 5 tools and manually aligning timestamps.
Every Search Starts from Zero
Grep has no memory. Each command discards everything you learned from the previous one. Your investigation state lives only in your head.
Senior Engineers Are the Bottleneck
Only engineers with 5+ years of platform experience can debug cross-layer issues. Everyone else escalates and waits.
How Deep Research Investigates
A multi-step autonomous agent that reasons about your system — not just your logs.
Multi-Step Investigation
Deep Research plans an investigation strategy, executes multiple searches, and refines its approach based on what it discovers. If the first hypothesis doesn't hold, it pivots.
Follow-Up Questions
Drill deeper into any finding. Deep Research retains full context from previous steps, so follow-ups build on what's already been discovered.
Cross-Layer Reasoning
Traces cause-and-effect chains across logcat, dmesg, bugreport sections, and telecom traces. Connects events that span system layers and time windows.
Shareable Reports
Every investigation produces an organized report: root cause, supporting evidence from log lines, causal chain, and actionable recommendations. Share via link — no account required.
Before vs After Deep Research
Before: Manual Investigation
- Open bugreport, start with grep for 'crash' or 'fatal'
- Find a crash → manually trace the stack through logcat, dmesg, dumpsys
- Align timestamps across sections to correlate events
- Search for related kernel messages in a separate window
- Check AOSP source code for the failing component
- Repeat for each hypothesis — 4-8 hours per complex issue
After: Deep Research
- Upload logs, ask 'Why did this device reboot?'
- Deep Research traces the crash through framework → kernel → driver
- Correlates thermal events, memory pressure, and OOM kills automatically
- Identifies the thermal driver triggering emergency shutdown at 95°C
- Links to upstream kernel patch that raises the threshold
- Complete root-cause report — 3 minutes
Real Investigation: Random Reboot on Pixel Device
A user reports their device reboots randomly during video playback. Here's what Deep Research finds:
- 1User asks: 'Why did this device reboot during video playback?'
- 2Step 1: Deep Research finds system_server crash in logcat with SIGSEGV in SurfaceFlinger
- 3Step 2: Traces to hardware composer HAL returning invalid buffer handle after thermal throttling
- 4Step 3: Correlates with dmesg showing GPU frequency scaling event at the same timestamp
- 5Step 4: Identifies thermal driver reducing GPU clocks below minimum required by active codec
- 6Step 5: Links to upstream kernel commit that fixes the frequency floor for active video decode
- ✓Result: Root cause identified in 2 minutes. Manual debugging would have taken 4+ hours.
See It in Action
Watch Deep Research trace a cross-layer system failure from symptom to root cause.
Multi-Step Investigation
AI autonomously searches, correlates, and builds a comprehensive report
WindowManager ANR trace
Works Across Every Log Type
Deep Research understands the structure and semantics of every format — and correlates across them.
Android Logs
Bugreports, logcat, ANR traces, tombstones, and dumpsys from phones, tablets, IVI, and IoT devices
Linux / Kernel Logs
Dmesg, kernel panics, driver probe failures, device tree issues, and syslog across ARM, x86, and RISC-V
Telecom Logs
Modem diagnostics, NAS/RRC protocol traces, QXDM exports, and RIL logs from Qualcomm, MediaTek, and Samsung basebands
Automotive Logs
CAN bus traces, VHAL events, CarService logs, and cross-ECU diagnostic data from Android Automotive
Who Uses Deep Research
Engineers across every vertical rely on Deep Research to solve their hardest debugging problems.
Device & Platform Engineers
Debug cross-layer issues across kernel, drivers, and framework on phones, tablets, and IoT devices. Deep Research connects the dots across system boundaries.
Telecom & Modem Engineers
Investigate NAS/RRC failures, call drops, and protocol signaling issues across modem diagnostic logs. Deep Research correlates RIL events with network state transitions.
Automotive Engineers
Trace CAN bus floods, VHAL callback storms, and IVI crashes across the full vehicle software stack. Deep Research connects ECU diagnostics with Android Automotive logs.
Found an issue? See what changed.
Use Delta to compare logs across builds and isolate the regression that introduced it. Deep Research tells you why it happened. Delta tells you what changed.
Frequently Asked Questions
Everything you need to know about Deep Research.
Deep Research is the autonomous investigation engine at the heart of logcat.ai. Instead of returning a single search result, it plans an investigation, runs multiple targeted queries, correlates findings across system layers, and produces a structured report with root cause analysis and recommendations.
Quick Search gives you a fast, single-pass answer to straightforward questions — great for 'what version is this device?' or 'show me the crash stack trace.' Deep Research is for complex investigations that require multiple search steps, hypothesis testing, and cross-referencing across different log sections.
Yes. After the initial investigation completes, you can ask follow-up questions that build on the previous findings. Deep Research retains full context from the investigation, so follow-ups are faster and more targeted.
Most investigations complete in 30 to 90 seconds, depending on the complexity of the question and the size of the log files. You can watch the progress in real-time as the AI executes each investigation step.
Deep Research works with all log types supported by logcat.ai: bugreports, logcat files, dmesg/kernel logs, and telecom diagnostic exports. It understands the structure of each format and can correlate events across different log types.
Deep Research is included in enterprise deployments and pilot engagements. Contact sales to discuss packaging, usage expectations, and access for your team.
Stop debugging manually. Start investigating.
Upload your logs, ask a question, and let Deep Research trace the root cause across every system layer