DPDP Compliant AI
Deploy DPDP-compliant AI without exposing personal data in your pipeline
Protecto is the layer between your data and the AI you use, identifying and masking sensitive data before it reaches LLMs, RAG systems, and agentic AI pipelines. Built to enforce DPDP compliance without breaking context or model accuracy.
- SOC 2 Certified
- ISO 27001
- DPDP DPA Ready
- Trusted by Engineering Teams Building AI at Scale
INR 250Cr
Maximum DPDP penalty for failing to take reasonable security safeguards to prevent a personal data breach
99%
Recall on sensitive data detection in multilingual unstructured text, including financial and health records
90%
Reduction in AI infrastructure costs for a SaaS customer processing 13 million long-form texts per day
9%
Of surveyed Indian organisations report a comprehensive understanding of the DPDP Act
The DPDP Compliance Gap
DPDP violations in AI pipelines start with architecture
Every RAG system, LLM integration, and agentic AI workflow that touches Indian personal data is now part of your DPDP risk surface. The challenge is not policy drafting. It is data flow. Personal data moves from KYC journeys, claim systems, CRM records, and support logs into prompts, embeddings, and model outputs without consent lineage, log retention, or deletion controls unless the architecture enforces them by default.
INR 250 crore
Digital Personal Data Protection Act, 2023. Schedule item for failure to take reasonable security safeguards to prevent personal data breach. India notified the core DPDP obligations, breach response, and penalty provisions to commence on May 13, 2027. AI teams that cannot prove consent, retention, access control, and breach handling on day one will face board scrutiny immediately.
RAG pipelines ingest Aadhaar, PAN, and claim data without purpose controls
Retrieval layers pull KYC documents, discharge summaries, and customer histories into prompts far beyond the original business purpose. Under DPDP, that expands processing beyond what the notice and consent flow justified.
No lineage means correction and erasure requests stall in AI systems
DPDP gives data principals rights to access, correction, and erasure. Most AI stacks cannot trace where one record lives across prompts, vector stores, caches, and response logs.
Third-party LLM calls break DPDP transfer and processor controls
When AI agents send raw personal data to external model providers, your processor contracts, board notices, and transfer restrictions all come into play at once. DPDP Section 16 lets the government restrict transfers to notified territories.
Breach response collapses without 72-hour board notice and one-year logs
DPDP Rules require notice to the Board within 72 hours and logs retained for one year to investigate unauthorised access. Generic LLM gateways do not create those records.
How it works
Three steps to DPDP-safe AI
Protecto sits between your data sources and your AI models. No pipeline rebuilds. No code rewrites. DPDP compliance is enforced at the infrastructure layer, not left to every application team to re-implement.
Detect personal data automatically
Protecto scans unstructured text, documents, API payloads, and database fields in real time. It identifies personal data relevant to DPDP workflows, including names, emails, phone numbers, Aadhaar references, PAN details, account data, medical records, and consent-linked identifiers across healthcare, financial services, and SaaS pipelines.
Mask with Context Preserved
Context-preserving masking replaces DPDP-regulated personal data with semantically coherent tokens. Your LLM receives usable text, not blanks. Model quality stays intact. Personal data does not reach the model layer, the prompt, or the external API call in raw form.
Govern, Audit, and Report
Every interaction with DPDP personal data is logged in an immutable audit trail. Export access records, breach-response evidence, and processor documentation on demand. Enforce access, correction, erasure, and retention workflows without rebuilding your application stack.
Platform Capabilities
Built for DPDP Compliant AI
Protecto implements DPDP technical requirements at the data pipeline level. Not a policy checklist. Engineering-grade controls that security leaders, compliance officers, and CTOs can document before enforcement starts.
Sub-sec
Real-time token generation for live pipelines
Billions
Rows handled via bulk API for migrations
50M+
PHI records processed for a single healthcare customer
Personal data detection
Identifies personal data in unstructured text, documents, KYC packets, claim notes, support logs, and API payloads. Covers the data classes DPDP teams worry about most: identifiers, contact data, financial records, health data, consent-linked events, and free-text personal information.
Context-Preserving Masking
Replaces DPDP personal data with semantically coherent tokens before data enters LLMs or RAG systems. Unlike redaction, Protecto preserves structure and meaning. LLM output quality stays intact while Rule 6 security safeguards are applied through masking and virtual-token controls.
Context-Based Access Control
Enforces least-necessary access at the AI layer. Each agent, user, or workflow accesses only the personal data justified for that task. Policy-driven controls prevent purpose drift, over-sharing, and uncontrolled unmasking across multi-agent and multi-tenant architectures.
Immutable Audit Logs
Every access to DPDP personal data is logged with timestamp, requesting entity, policy result, masking action, and output trace. Logs are tamper-resistant and exportable. Protecto supports the visibility, monitoring, review, and one-year retention requirements set out in the DPDP Rules.
DPDP processor contract ready
Protecto operates with Data Processor contract controls that map to DPDP fiduciary obligations. A standard DPA is available with every enterprise deal. Protecto does not train models on customer data. Contractual terms define processor safeguards, breach notice workflows, and audit expectations.
India-ready deployment options
Deploy Protecto on-premises, in a private cloud, or in a controlled regional environment. Personal data can stay within your perimeter before any third-party model sees the request. That supports DPDP transfer governance and India-based operating controls for significant data fiduciaries.
Customer Story
A healthcare insurer protected 50M+ records and unlocked $30-60M in annual AI value with Protecto
A major health insurance provider needed a privacy-preserving recommendation assistant across more than 50 million structured and unstructured records. The data included member identifiers, clinical context, and other personal data that could not be exposed to downstream AI systems.
Two privacy products had already failed on accuracy and scale. Manual remediation was projected to take six to nine months and cost more than $1 million before the AI product could even launch.
Protecto Vault delivered context-preserving masking, real-time prompt and response protection, and async APIs for RAG-scale processing. The result was a DPDP-ready architecture that kept personal data governed without breaking recommendation quality.
50M+
Structured and unstructured records protected across the AI application
$30-60M
Estimated annual value enabled by the AI project after Protecto deployment
6-9 mos
Of remediation time avoided versus the original privacy-readiness estimate
$1M+
In projected remediation spend avoided before launch
Health Insurance Provider
Healthcare and insurance teams use this pattern when they need AI on sensitive records without exposing raw personal data to model providers or downstream agents.
Recommendation AI. 50M+ records. Privacy-preserving RAG.
Built for Regulated Industries
DPDP compliance built for your industry
Every industry processes Indian personal data differently. Protecto maps its DPDP detection, masking, and governance capabilities to the data flows and obligations that matter in your sector.
Healthcare
Healthcare and Life Sciences
Hospitals, payers, digital health platforms, and diagnostics teams run AI on patient support logs, intake forms, member records, and claims documents. Protecto applies DPDP controls to high-volume healthcare workflows without breaking clinical or operational context.
Financial Services
Financial Services and Banking
Banks, lenders, insurers, brokers, and fintechs run AI across KYC, underwriting, collections, fraud, and customer service. Protecto keeps PAN, Aadhaar-linked references, account details, and narrative customer data governed under DPDP while still supporting low-latency model calls.
Enterprise AI
Enterprise SaaS and AI Companies
Enterprise SaaS companies shipping copilots, support agents, and RAG experiences need DPDP compliance before customer data is embedded or sent to third-party models. Protecto wraps those AI layers with masking, access policy, and traceable unmasking so product teams can ship faster.
Why Protecto
Not all data masking tools are built for DPDP-compliant AI
Generic redaction and cloud NLP tools were designed for simpler detection use cases, not DPDP AI pipelines. Here is how Protecto compares on the controls that Indian compliance, security, and engineering teams actually evaluate.
| DPDP capability | Protecto | AWS Comprehend | Generic Masking / DSPM |
|---|---|---|---|
| Context-preserving masking for LLMs | ✓ Yes | ✕ No | ✕ No |
| Detection accuracy on Indian unstructured text | ✓ 99% recall, 96% precision | ! PII detection only, no Protecto-style benchmark | ! Variable, rules-based |
| DPDP-ready processor agreement | ✓ Yes, signed as standard | ✓ AWS DPA available | ! Varies by vendor |
| Context-based access control for AI agents | ✓ Yes | ✕ No | ✕ No |
| Immutable audit logs for board investigations | ✓ Yes, exportable pipeline logs | ! Partial, CloudTrail is generic | ✕ No |
| On-premises and India data residency deployment | ✓ Yes | ✕ No, managed service default | ! Varies |
| RAG and agentic AI pipeline support | ✓ Yes, native pipeline integration | ! Limited, document-level only | ✕ No |
Certifications
Compliance Built In. Not Bolted On.
Protecto holds the certifications and operating controls that DPDP procurement, legal review, and security teams expect. Documentation is available at procurement stage without a full sales process.
SOC 2 Type II
Independently audited security, availability, and confidentiality controls. Annual renewal. Supports the technical and organisational safeguards DPDP expects around personal data processing.
ISO 27001
Certified information security management system covering data handling, access controls, risk management, and incident response. Useful evidence for DPDP security review and vendor diligence.
DPDP DPA ready
Standard Data Processing Agreement available at procurement stage. Protecto supports fiduciary-processor operating models and documents processor safeguards, escalation paths, and breach workflows up front.
India governance support
Protecto supports India-based operating models with audit exports, breach-notice evidence, and deployment options that help significant data fiduciaries align with DPO, audit, and transfer obligations.
Common Questions
DPDP Compliance Questions, Answered
Does Protecto sign a DPDP Data Processing Agreement?
Does Protecto train its models on customer data?
How does Protecto handle DPDP breach notice and log-retention requirements?
Can Protecto be deployed on-premises for India data residency requirements?
How does context-preserving masking differ from standard redaction?
How quickly can Protecto integrate into an existing DPDP AI pipeline?
See Protecto detect and mask personal data in your pipeline. Live.
30 minutes. A solutions engineer. Your data type. No slides. No sales pitch. We connect to your pipeline and run Protecto on your actual workflow so you can verify DPDP detection accuracy, masking quality, and audit outputs before any commitment.
- SOC2 Certified
- ISO 27001
- DPDP DPA Ready