Blog · Category

AI in QA

AI-native test automation for regulated enterprises, without the data-egress problem. These articles show how banking, insurance, healthcare, and government QA teams run AI test authoring, self-healing selectors, and root-cause analysis on a bring-your-own-LLM endpoint they control, so test data and prompts never leave their perimeter, aligned with DORA, HIPAA, PCI-DSS, and FedRAMP.

AI test automation without data egress for regulated QA teams — architectural diagram contrasting public cloud LLM APIs (OpenAI, Anthropic) leaking DOM and session data outbound versus Element34 SBOX contained inside the enterprise perimeter with local vLLM/NIM inference, local RAG vector database, and private execution grid for HIPAA, GDPR, DORA, PCI-DSS, and FedRAMP compliance

AI Test Automation Without Data Egress: How Air-Gapped LLM Test Authoring Actually Works

Regulated QA teams don't have to choose between AI and data containment. See how air-gapped LLM test authoring keeps every byte behind the firewall.