End-to-End AI Testing & DeepEval QA

Automating evaluation metrics, agent trajectory validation, and regression suites for enterprise Chatbots, RAG Pipelines, and Model Context Protocol (MCP) servers.

DeepEval AI QA Automation & RAG Metric Evaluation Pipeline

RAG Pipeline Evaluation

Measuring retrieval precision and response accuracy with production thresholds.

Faithfulness Metric (Hallucination detection)
Answer Relevancy & Contextual Relevancy
Contextual Precision & Contextual Recall

Agent Trajectory & Tool Calling

Verifying multi-step agent reasoning and deterministic API invocation.

Tool Call Correctness (Pydantic schema validation)
Exact Trajectory Step Tracing & Loop Prevention
Sub-agent task delegation consistency

MCP Server QA & Protocol Compliance

Testing Model Context Protocol tool interfaces for safety and reliability.

JSON-RPC 2.0 schema adherence validation
Resource uri-template resolution checks
Prompt injection resistance & sandbox escapes

Red-Teaming & Safety Guards

Probing generative models against adversarial prompts and jailbreaks.

Prompt Injection & System Prompt Extraction
PII & Sensitive Corporate Data Leakage
Toxicity, Bias & Hallucination Stress Testing

        // Automated DeepEval PyTest CI/CD Pipeline Example
        
import pytest
from deepeval import assert_test
from deepeval.test_case import LLMTestCase
from deepeval.metrics import FaithfulnessMetric, AnswerRelevancyMetric

def test_rag_pipeline_accuracy():
    retrieved_context = ["Gene Da Rocha is an AI Systems Engineer specializing in DeepEval testing and RAG pipelines."]
    actual_output = "Gene Da Rocha is an AI Systems Engineer who builds RAG evaluation suites."
    
    test_case = LLMTestCase(
        input="What does Gene Da Rocha specialize in?",
        actual_output=actual_output,
        retrieval_context=retrieved_context
    )
    
    faithfulness = FaithfulnessMetric(threshold=0.85)
    relevancy = AnswerRelevancyMetric(threshold=0.85)
    
    assert_test(test_case, [faithfulness, relevancy])
        
      

RAG Pipeline Evaluation

Agent Trajectory & Tool Calling

MCP Server QA & Protocol Compliance

Red-Teaming & Safety Guards

Implement Automated AI QA in Your Pipeline