AI Internal Knowledge Search - Company Brain Platform
Manual and Automation QA Engineer
Problem Statement
Enterprises struggled with knowledge silos where critical information was scattered across documents, emails, Notion pages, and various repositories. Employees spent hours searching for answers, leading to reduced productivity and inconsistent information retrieval.
Approach & Solution
Designed and executed comprehensive test suites for RAG pipeline accuracy, document ingestion workflows, semantic search relevance, and multi-source data synchronization. Validated context retrieval, answer generation quality, and source citation accuracy.
Testing Strategy
Collaborated with AI/ML engineers to test vector embedding quality, retrieval precision, and LLM response accuracy. Performed integration testing for Google Workspace, Outlook, Notion, and Confluence connectors. Conducted load testing to ensure scalability across large document corpuses.
CI/CD Integration
Integrated automated API tests with Jenkins for continuous validation of search relevance, document indexing accuracy, and RAG pipeline performance. Set up monitoring for query latency, retrieval accuracy, and hallucination detection.
Code Implementation
@pytest.mark.asyncio
async def test_rag_search_accuracy():
"""Test RAG pipeline returns accurate, sourced answers."""
query = "What is our company's remote work policy?"
response = await client.post(
"/api/v1/knowledge/search",
json={"query": query, "sources": ["notion", "docs", "email"]},
headers={"Authorization": f"Bearer {API_TOKEN}"}
)
assert response.status_code == 200
result = response.json()
# Validate answer structure
assert "answer" in result
assert "sources" in result
assert len(result["sources"]) > 0
# Validate source citations
for source in result["sources"]:
assert "document_id" in source
assert "title" in source
assert "relevance_score" in source
assert source["relevance_score"] >= 0.7
# Validate response time
assert response.elapsed.total_seconds() < 2.0Results & Impact
Achieved 92% answer accuracy with proper source citations. Reduced average information retrieval time from 45 minutes to under 30 seconds. Successfully indexed 500K+ documents across multiple data sources with 99.5% sync accuracy.