Project Niti – Google Gen AI Safety

Multilingual AI Safety & Policy Reinforcement

Responsible AI · Multilingual Data Systems · Safety Evaluation · Policy Robustness · Expert Networks
PING executed a multilingual AI safety data program aligned with national AI objectives, focused on strengthening large language model resilience against harmful or adversarial content.
The initiative required structured coordination of domain experts and rigorous dataset governance.

  • Activated 45 language experts
  • Covered 9 Indian languages
  • Delivered structured adversarial datasets aligned to safety policies
  • Ensured compliance with policy and content integrity guidelines
  • Coordinated quality validation and submission workflows

The program strengthened model robustness through diverse linguistic and contextual inputs.
The Impact

  • Enhanced multilingual model resistance
  • Improved safety benchmarking frameworks
  • Built scalable expert-driven data pipelines

PING operates at the intersection of AI systems, language diversity, and operational precision.

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