Data labeling & annotation
Consistent, guideline-driven classification and annotation with quality controls for complex datasets.Expected outcome: structured feedback loops that improve model accuracy over time.
Human-in-the-Loop AI/ML
Human judgment for better AI.
Your AI support tools are making decisions your team has never reviewed. We add the human layer that catches errors before they reach customers, feeds corrections back to the model, and keeps your AI system aligned to EU AI Act, ISO 42001, and NIST AI RMF expectations.
Discuss your AI workflow The human layer
AI governance needs human judgment, not just automation.
Our specialists support the workflows that shape model performance before deployment and safeguard it in production.
Model evaluation
Structured human assessment of relevance, accuracy, safety, tone, and task completion.Expected outcome: consistent review criteria across high-risk AI use cases.
Bias detection
Targeted review across scenarios and cohorts to identify systematic performance gaps and harmful patterns.Expected outcome: gaps identified before they become customer-facing problems.
AI response validation
Human review of generated outputs against policy, factuality, brand, and customer experience standards.Expected outcome: 20–30% faster response drafting time and improved consistency.
Test case creation
Scenario libraries, edge cases, and evaluation sets designed around real-world use and failure modes.Expected outcome: better pre-release testing for rare but high-impact scenarios.
Automation monitoring
Ongoing exception review, escalation, and feedback loops that improve production reliability.Expected outcome: systemic AI errors detected 3–7 days before customer impact.
Make quality operational
Add the right human layer to your AI system.
Tell us about your model, workflow, and quality goals.
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