Quality Assurance Bot

A specialized AI agent designed to ensure overall testing quality, validate test results, and provide comprehensive quality assurance oversight across all testing activities. This agent excels at quality validation, visual testing analysis, and ensuring testing standards and best practices are maintained. Key Capabilities: - Analyzes visual testing results and identifies UI/UX issues - Validates test coverage and testing quality across all phases - Ensures testing standards and best practices are maintained - Provides quality metrics and improvement recommendations - Coordinates quality assurance activities across testing teams - Integrates with Slack for quality updates and notifications - Maintains testing quality standards and compliance requirements

LIVE

Test Agent

Purpose

AI-Powered Intelligence — Advanced AI capabilities for automated processing and analysis

Enterprise Ready — Built for production with security, scalability, and reliability

Seamless Integration — Easy to integrate with your existing systems and workflows

Agent Capabilities

This agent is equipped with the following advanced capabilities:

Knowledge Base

Vector search & retrieval

Knowledge (NoneType)

Available Tools

Test Visual Diff Summary Tool

Parse un résultat de visual testing type Applitools-like (JSON simplifié). Input: {"results":[{"name":"page X","diff_pct":1.2,"status":"passed|failed"}]} Returns: {"passed":N,"failed":N,"avg_diff_pct":X}

def test_visual_diff_summary_tool(json_text: str) -> Dict[str, Any]:
    """
    Parse un résultat de visual testing type Applitools-like(JSON simplifié).
    Input: {"results":[{"name":"page X","diff_pct":1.2,"status":"passed|failed"}]}
    Returns: {"passed":N,"failed":N,"avg_diff_pct":X}
    """
    data = _extract_json(json_text) or {}
    results = data.get("results", []) or []
    passed = sum(1 for r in results if str(r.get("status", "")).lower() == "passed")
    failed = sum(1 for r in results if str(r.get("status", "")).lower() == "failed")
    diffs = [_to_number(r.get("diff_pct", 0)) for r in results]
    avg = round(sum(diffs) / len(diffs), 2) if diffs else 0.0
    return {"passed": passed, "failed": failed, "avg_diff_pct": avg}

Reasoning Tools

ReasoningTools from agno framework

Required Inputs

Generated Outputs

Business Value

• Automated processing reduces manual effort and improves accuracy

• Consistent validation logic ensures compliance and audit readiness

• Early detection of issues minimizes downstream risks and costs

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Pricing

Get in touch for a tailored pricing

Custom Deployment

Tailored to your organization's specific workflows and requirements.

Enterprise Support

Dedicated support team and onboarding assistance.

Continuous Updates

Regular updates and improvements based on latest AI advancements.

For enterprise deployments.

€Custom

one time payment

plus local taxes

Contact Sales

Tailored solutions — Custom pricing based on your organization's size and usage requirements.

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