ZENXDATA / AI INTELLIGENCE, APPLIED
Make AI performance measurable.
AI evaluation, testing, benchmarking and human intelligence. Evidence for the decisions that take your AI from promising to production.
From uncertainty to evidence
Your AI works in a demo.
What happens in the real world?
We help teams uncover failure modes, measure model quality and improve the data behind their systems. Structured testing. Human judgment. Findings your engineers can act on.
Our capabilities
Build. Test.
Improve. Scale.
A focused evaluation sprint or a long-term data program. The right expertise, around your AI.
Evaluation & benchmarking
Custom benchmarks, human evaluation and clear evidence for your next model decision.
Testing & red teaming
Find safety, reliability and prompt-injection failures before your users do.
AI data & human intelligence
Domain-specific datasets, expert feedback and quality-controlled data programs.
Agent & workflow reliability
Test tool calls, multi-step tasks and recovery in the workflows that matter.
Also supporting speech & audio ai, multimodal ai, managed ai workforce.
Explore all servicesWhat can we test?
What can we test?
Tell us what you are building. We'll help identify the evaluation, data, or testing services relevant to your project.
Pick at least one option in each list to see matching services and programs.
Prefer to talk first?
The way we work
Not another score.
A clearer decision.
We start with the question your team needs to answer. Then build the test plan, apply quality controls and deliver evidence—not unexplained numbers.
Inside our methodology- 01
Define the decision
Align on your use case, risk profile, coverage and acceptance criteria.
- 02
Test with rigor
Run structured evaluations with calibrated rubrics and review checkpoints.
- 03
Deliver the evidence
Reproducible failures, quality findings and prioritized next steps.
See what a deliverable can look like.
View illustrative evaluation reportPerspectives
Thinking you can act on.
LLM evaluation: a practical guide for product teams (2026)
What LLM evaluation is, which methods to use, how to build a golden set, and how to turn scores into a ship / don't-ship decision.
How to test AI agents before launch: a pre-deployment checklist
Agents fail differently from chatbots. A step-by-step checklist for testing tool use, multi-step reliability, prompt injection and recovery before real users arrive.
RAG evaluation: how to measure retrieval and answer quality
Retrieval-augmented generation fails in two places — retrieval and generation. The metrics and test sets that tell you which one is broken.
ZenXData AI Tools Index
A better starting point for your next AI decision.
Explore tools, official sources and published evaluations.
Your next step
Let's build confidence in your AI.
Send us what you are building. We will scope the data, evaluation, benchmarking or testing program and come back with a proposal.