Data-Centric Engineering
Engineering has always been a profession of pragmatic decision-making under uncertainty. What’s changed is the toolkit: scalable probabilistic inference, […]
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assurance-focused AI
De-risking complex models
for the real world.
AQ provides independent assurance and verification for data-centric solutions in engineering. To ensure they are trustworthy, explainable and fit for purpose.
# verify and validate your ML workflow
from aq import AssuranceClient
client = AssuranceClient(model=your_ml_pipeline)
report = client.validate(
method='verification',
standard='industry_best_practice'
)
print(report.actionable_guidance)
// TRUSTED BY
// what we do
Assurance for
data-centric engineering.
Engineering tools are advancing. Assurance frameworks are not. AQ closes that gap.
01
Assurance
Verifying that models, workflows and software do what they claim to do.
- -> Verification & Validation
- -> Workflow inspection
- -> Software, modelling & data processing
02
Uncertainty-aware engineering
Quantifying what is known, unknown, and unknowable in complex systems.
- -> Probabilistic modelling
- -> WALD decision tool
- -> Decision analysis
03
Best practice
Building the standards and skills that let organisations deploy complex models safely.
- -> Guidance & standards
- -> Training & education
- -> Risk-informed policy
// latest thinking
From the blog
// work with us
Ready to de-risk your data-centric engineering?
Whether you need a full verification audit or expert training for your team, we'd love to hear about your project.
start_project()