> ## Documentation Index
> Fetch the complete documentation index at: https://docs.contextual.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Device Log Analysis Agent

> AI agent for automated root cause analysis of device logs (wireless, ATE, infotainment)

## Overview

**Powered by the [Device Log Analysis](/how-to-guides/agent-composer-templates#device-log-analysis-enterprise) template** in [Agent Composer](/quickstarts/agent-composer)—Enterprise; [request a demo](https://contextual.ai/request-a-demo).

Root cause analysis (RCA) for device logs. The agent parses logs, cross-references debug rules, and generates RCA reports—work that would otherwise take a senior engineer hours manually. **Demo log files are synthetic** (created for this demo); download them from the live demo and try the same workflow in your own environment.

The **[live demo](https://demo.contextual.ai/log-analysis)** includes **three sample datasets**—each is a log plus matching debug reference for a different scenario. Run one of the suggested queries (or your own). For more Agent Composer demos beyond DLA, see **[Contextual AI Demos](/examples/overview-demos)**.

<Note>
  **Demo behavior:** Refreshing the page will clear your progress. For this demo, queries are cached and sped up (production DLA template).
</Note>

## Try the Demo

<Card title="Launch Demo" icon="tower-cell" href="https://demo.contextual.ai/log-analysis">
  Analyze device logs yourself
</Card>

## Sample datasets in the demo

The live demo offers **three** preloaded options—each is a **pair** of synthetic files (device log + debug reference). Use the links below for scenario-specific example questions, example outputs, and file descriptions.

<CardGroup cols={3}>
  <Card title="3GPP Wireless" icon="tower-cell" href="/examples/3gpp-wireless-log-analysis">
    LTE-style eNB/RRH logs, handovers, CPRI/HARQ/BLER. Example: "Why did the calls drop?"
  </Card>

  <Card title="ATE Board Validation" icon="microchip" href="/examples/ate-log-analysis">
    Multi-site test logs, VR telemetry, DDR5/PCIe. Example: "Why did SITE:2 fail?"
  </Card>

  <Card title="Mazda Infotainment" icon="car" href="/examples/mazda-infotainment-log-analysis">
    CMU crash logs, format-string-style bugs. Example: "Why did my car stereo restart?"
  </Card>
</CardGroup>

## The Problem

When a device or network incident occurs, engineers must manually sift through thousands of timestamped log entries containing cryptic error codes, protocol abbreviations, and vendor-specific identifiers. Root cause analysis requires:

* Decoding error codes against reference documentation
* Correlating events across subsystems
* Building timelines to establish causality between failures
* Identifying patterns across multiple failure events
* Distinguishing symptoms from root causes

## How It Works

### In production

**What you do:** Upload a **log file** and optionally **additional context** (e.g. a debug reference guide), then ask a query—for example *"Why did the call drop?"*.

**What happens automatically:** A multi-agent implementation takes over. The system breaks the work into **tasks**, shows **trajectory** as agents run, **parses** the logs, **builds searchable databases** from the log and reference files, runs root cause analysis, and produces outputs.

**Pipeline stages:** Uploading files → parsing logs → building the database → root cause analysis → generating the report.

**Outputs:** The agents can **generate Python scripts** (e.g. custom parsers) that run in a secure **VM**, produce **visuals** (causation timelines, degradation charts), and deliver a **detailed RCA report** (executive summary, timeline, decoded errors, recommended actions).

**Auditable:** You specify the output (report, artifacts, visuals). Every step—tasks, trajectory, intermediate artifacts, and final report—is visible so teams can review and learn from the analysis.

### In this demo

**Three** demo datasets are **preloaded** (3GPP Wireless, ATE Board Validation, Mazda Infotainment). Each is a device log plus matching debug reference. See the dataset pages above for suggested queries and example outputs.

## Output

Each scenario produces a **detailed RCA report** and optional **visualizations**. Report content varies by domain but typically includes an executive summary, fault or session timeline, decoded errors, root cause chain, and prioritized recommended actions. For concrete example outputs and screenshots:

* **[3GPP Wireless](/examples/3gpp-wireless-log-analysis#output)** — Call drop causality, system health timelines, BER/BLER/HARQ comparisons
* **[ATE Board Validation](/examples/ate-log-analysis#output)** — VDDQ voltage/thermal charts, per-site comparison, tester artifact analysis
* **[Mazda Infotainment](/examples/mazda-infotainment-log-analysis#output)** — Incident timeline, crash sequence, format string vulnerability walkthrough

## Sample files in the demo

Each of the three datasets is a **pair** of synthetic files: a timestamped **device log** and a **debug reference guide**. The live demo loads all three so you can compare scenarios. For file names and contents per dataset:

* **[3GPP Wireless](/examples/3gpp-wireless-log-analysis#3gpp-wireless-sample-files-in-the-demo)** — `3gpp_wireless_device_log.txt`, `3gpp_wireless_debug_rules.txt`
* **[ATE Board Validation](/examples/ate-log-analysis#ate-sample-files-in-the-demo)** — `ate_device_log_30mb.txt`, `ate_debug_rules.txt`
* **[Mazda Infotainment](/examples/mazda-infotainment-log-analysis#mazda-sample-files-in-the-demo)** — `mazda_device_log_30mb.txt`, `mazda_debug_rules.txt`

## Learn More

* [Contextual AI Demos](/examples/overview-demos) — Other live demos (spec search, materials, test automation, and more)
* [Getting Started with the Contextual AI Platform](/quickstarts/getting-started)
* [Example: Device Log Analysis (Enterprise)](/quickstarts/why-contextual-ai#example-device-log-analysis-enterprise) — How multi-source root cause analysis fits the platform
* [Agent Composer Templates](/how-to-guides/agent-composer-templates) — Basic Search, Agentic Search, and Device Log Analysis (Enterprise)
* [Request a demo](https://contextual.ai/request-a-demo)