Quality & Security
Production AI requires data you can trust.
Quality is a process with measurable gates, not a promise. Security and governance are designed in from day one — auditable, isolated, and customer-owned.
01 / 05
Quality System
Quality you can operationalize — not a promise, a process with measurable gates.
10 controls
- Expert qualification
- Training and calibration
- Gold tasks
- Inter-annotator agreement
- Consensus review
- Escalation paths
- QA sampling plans
- Error taxonomy
- Drift monitoring
- Continuous improvement
02 / 05
Expert Network
Qualified specialists across the domains and modalities your model depends on.
7 controls
- Domain experts
- Language specialists
- STEM experts
- Medical / legal / finance experts
- Robotics operators
- Data reviewers
- Evaluation specialists
03 / 05
Data Governance
Every dataset is traceable, versioned, and auditable end to end.
6 controls
- Data lineage
- Dataset versioning
- Annotation history
- QA audit trail
- Guideline version control
- Client review history
04 / 05
Security & Compliance
Designed for enterprise-grade security and compliance workflows.
10 controls
- Role-based access control
- NDA workflows
- Data isolation
- Secure workspaces
- Audit logs
- Encryption in transit and at rest
- PII de-identification
- Data retention policies
- SOC 2 / ISO 27001 readiness roadmap
- GDPR-ready workflows
05 / 05
Responsible AI
An ethical workforce and a responsible-AI posture built into every engagement.
6 controls
- Responsible AI statement
- Ethical workforce standards
- Bias and fairness review
- Data usage rights
- Customer-owned training data
- Transparency in methodology
Compliance
Mapped to the frameworks your security team reviews.
SOC 2 and ISO 27001 readiness roadmap in progress. We complete security questionnaires as part of onboarding and align our controls to your standards.