Argus QA
KSA
Agentic AI
Prompt and execution tracking
Cloud Based Systems
Project Summary
The AI Quality Assurance platform is an intelligent validation system designed to evaluate and monitor the performance of AI solutions. It assesses modular components and complete AI systems—including RAG and standalone models—across key quality metrics such as accuracy, hallucination, relevance, toxicity, faithfulness, and bias. With features like prompt evaluation, execution tracking, and interactive dashboards, the platform ensures reliable, transparent, and consistent AI performance throughout development and deployment.
Business Impact
  • Improved AI reliability | Reduced evaluation effort | Enhanced transparency and trust | Consistent model performance tracking | Accelerated AI deployment cycles
Business Requirements
  • Validate AI model performance | Ensure reliability and transparency | Detect hallucination and bias | Standardize AI quality metrics | Monitor end-to-end AI lifecycle
Delphi Solutions
  • AI Quality Assurance platform | Automated model evaluation framework | Prompt and execution tracking | Interactive performance dashboards | Multi-metric AI assessment engine
Challenges
Understanding the Challenges
AI systems lacked standardized evaluation methods, making it difficult to ensure reliability, accuracy, and transparency across deployments.
Inconsistent Quality Metrics
Different teams used varying benchmarks, resulting in unclear standards for assessing AI model performance.
Limited Visibility into Model Behavior
Organizations struggled to detect issues like hallucination, bias, and toxicity within complex AI workflows.
Manual and Fragmented Evaluation Processes
AI validation lacked automation and integration, slowing development and reducing confidence in model outcomes.
SOLUTION
Crafting Tailored Solutions
An intelligent AI Quality Assurance platform was built to automate, standardize, and monitor AI evaluation end-to-end.
Unified Evaluation Framework
Introduced a centralized system to assess AI models using consistent quality metrics across all components.
Comprehensive Performance Tracking
Enabled continuous monitoring of accuracy, relevance, and bias through automated testing and prompt analysis.
Interactive Dashboards and Insights
Delivered transparent, real-time visibility into AI performance via analytics dashboards and detailed reporting tools.
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Argus QA

Industry

KSA
Agentic AI
Prompt and execution tracking
Cloud Based Systems

Location

KSA
Agentic AI
Prompt and execution tracking
Cloud Based Systems

Technology

KSA
Agentic AI
Prompt and execution tracking
Cloud Based Systems

Project Overview

The AI Quality Assurance platform is an intelligent validation system designed to evaluate and monitor the performance of AI solutions. It assesses modular components and complete AI systems—including RAG and standalone models—across key quality metrics such as accuracy, hallucination, relevance, toxicity, faithfulness, and bias. With features like prompt evaluation, execution tracking, and interactive dashboards, the platform ensures reliable, transparent, and consistent AI performance throughout development and deployment.

Challenges

Understanding the Business Requirements

AI systems lacked standardized evaluation methods, making it difficult to ensure reliability, accuracy, and transparency across deployments.

Inconsistent Quality Metrics

Different teams used varying benchmarks, resulting in unclear standards for assessing AI model performance.

Limited Visibility into Model Behavior

Organizations struggled to detect issues like hallucination, bias, and toxicity within complex AI workflows.
SOLUTIONS

Understanding the Impact

An intelligent AI Quality Assurance platform was built to automate, standardize, and monitor AI evaluation end-to-end.

Unified Evaluation Framework

Introduced a centralized system to assess AI models using consistent quality metrics across all components.

Comprehensive Performance Tracking

Enabled continuous monitoring of accuracy, relevance, and bias through automated testing and prompt analysis.

Interactive Dashboards and Insights

Delivered transparent, real-time visibility into AI performance via analytics dashboards and detailed reporting tools.
IMPACT

Understanding the Impact

The redesign led to a 50% increase in online bookings and improved user satisfaction.

Increased Bookings

Online bookings increased significantly post-redesign.

Improved Satisfaction

User satisfaction levels rose due to the improved experience.
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