Overview

Not every defect makes a test fail.

A test can finish with a green “pass” while warnings, unusual readings, or incorrect settings remain undetected. These hidden issues can surface later, increasing troubleshooting effort and cost.

Mindteck’s AI Storage Defect Finder uses an agentic AI workflow to analyze test logs and system data after execution. It identifies unusual behavior, investigates potential causes, and consolidates findings into a single analysis for engineering review.

In simple terms: It works like a team of specialists that reviews test logs, learns from past findings, and highlights potential issues in minutes, while engineers remain in control of every decision.

What It Does

Intelligent Log Analysis

Filters errors, warnings, and unusual patterns across host, switch, and controller logs so engineers can focus on relevant findings.

AI-Based Anomaly Detection

Flags unexpected behavior, even when tests complete successfully without reporting errors.

Context-Aware Investigation

Specialized agents examine system configuration, connectivity, and client or workload behavior.

Historical Defect Intelligence

References similar past issues and investigation findings to reduce repeated troubleshooting.

Multi-Agent Orchestration

A central workflow engine coordinates specialized agents and combines their findings into one analysis.

Automated Triage Support

Summarizes engineering findings and supports defect or support ticket creation, subject to your review.

Challenges It Solves

Too Much Test Data

Automatically analyzes extensive logs and system data, reducing manual review effort.

Hidden Anomalies

Flags unexpected patterns that may remain undetected in passed test runs.

Fragmented Investigation

Brings together information from different logs and system data sources to help engineers understand what may be causing an issue, without reviewing each source separately.

Repeated Troubleshooting

Surfaces relevant historical findings to help engineers investigate recurring issues faster.

Delayed Defect Triage

Provides consolidated findings and potential causes to support faster investigation and ticket preparation.

How It Works

From test completion to engineering insight in six steps

Step 01

Collect Test Data

Gathers test, host, switch, and controller logs, plus configuration details and performance data, once the run ends.

Step 02

Parse and Structure

Turns raw, messy output into organized information that can be analyzed.

Step 03

Detect Anomalies

Applies AI/ML techniques to spot errors, unusual patterns, and potential defects.

Step 04

Investigate and Correlate

Specialized agents check configuration, connectivity, workload signals, and past findings.

Step 05

Generate Insights

Consolidates everything into a summary of potential issues and the evidence behind them.

Step 06

Support Defect Management

Helps create defect or engineering tickets through your configured workflow.

What Makes It Different

Beyond Pass/Fail Testing

Examines passed and failed runs to identify anomalies traditional test automation may miss.

Human-Controlled Decisions

Engineers review the analysis and approve next steps and ticket creation.

Designed to Evolve

Allows additional agents and analysis capabilities as requirements grow.

See What Your Passing Tests Are Missing

Help your engineering teams uncover hidden defects, investigate unusual behavior, and make better-informed decisions from test results.

Talk to Our Experts

Intelligent Defect Detection for Storage System Testing

Mindteck AI Storage Defect Finder