DPDP as an engineering input
The Digital Personal Data Protection Act requires Indian organizations to treat personal data with defined purpose, minimization, and accountability — all relevant when AI systems ingest support tickets, HR documents, or customer records.
Engineering teams should participate early in data mapping workshops, not after legal sends a blocker list.
Global-facing Indian SaaS companies must often satisfy DPDP and GDPR concurrently — design once with the stricter constraint in mind.
Checklist for RAG and agent systems
Define lawful basis and notice for each data source connected to retrieval indexes.
Enforce purpose limitation in connectors — do not index collections “just in case.”
Implement access mirroring so retrieval cannot expose documents a user could not open in source systems.
Document retention and deletion for embeddings, logs, and fine-tuning datasets.
Add human oversight paths for high-impact automated actions affecting data principals.
Shipping speed with defensible governance
Checklists should be embedded in sprint definitions of done: no new connector without owner, retention tag, and eval cases.
Bangalore-based engineering partners should deliver artifacts Indian enterprises can reuse in audits — not only working code.
Measured rollout beats big-bang launches: pilot with internal users, measure quality and privacy incidents, then expand.