
QA & Testing for AI Systems
We've been doing QA for 25 years. Now we're applying that discipline to the hardest testing challenge in modern software: non-deterministic AI systems.
This page is QA for AI systems. For AI-enabled software QA, see AI-Enabled SQA.
If you are looking to use AI to improve how you test software (automation generation, evidence capture, living regression suites), see our AI-Enabled SQA service. This page is about testing AI systems: evaluation harnesses, red-teaming, regression testing for LLMs.
Traditional QA assumes deterministic outputs. AI doesn't work that way.
25 years of QA discipline, applied to systems that can't be tested deterministically.
Real work at the intersection of QA and AI
Our team implemented an AI test generation tool for a major open-source foundation — real work at the intersection of decades of QA expertise and modern AI systems. The same combination of traditional QA discipline and AI-native understanding that Proticom applies to client engagements.
What we build
This page is QA for AI systems.
If you want to use AI to accelerate your software QA practice (case drafting into your tools, living automation, computer-use evidence), see AI-Enabled SQA.
Book a technical conversation — testing strategy starts with understanding what failure costs.
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