Faceoff Technologies Launches AI-Powered Privacy Management Platform to Help Indian Enterprises Prepare for DPDPA Compliance

Made-in-India platform unifies consent, Data Principal rights, privacy assessments, confidential-data discovery, breach management and compliance audits

NEW DELHI, INDIA — 10th July 2026; Faceoff Technologies, an Indian deep-technology company specializing in artificial intelligence and privacy engineering, today announced the launch of Faceoff Privacy, an AI-powered Unified Privacy Management Platform designed to help Indian enterprises operationalize and demonstrate compliance with the Digital Personal Data Protection Act, 2023 and the Digital Personal Data Protection Rules, 2025.

The platform has been designed for organizations that must manage growing privacy obligations without relying on fragmented software products, spreadsheets or recurring manual compliance exercises.

India’s Micro, Small and Medium Enterprise sector includes more than 7.47 crore enterprises, contributes approximately 31.1% of the country’s GDP and supports livelihoods for about 32.8 crore people. Many of these businesses process customer, employee, patient, financial, biometric and digital-behaviour data but do not have the legal, technical and compliance resources available to large multinational organizations.

Faceoff Privacy seeks to address this imbalance by providing an integrated and scalable privacy-management platform that can be deployed by enterprises of different sizes and across regulated industries.

“The real challenge is not simply understanding the DPDPA—it is demonstrating compliance. Organizations must be able to show that valid consent was captured, withdrawals were implemented, Data Principal requests were handled, breach timelines were monitored and personal data was appropriately protected. Faceoff Privacy is designed to make compliance operational and demonstrable rather than merely policy-driven.” Says, Dr. Deepak Kumar Sahu, Founder and CEO, Faceoff Technologies

 

Dr. Sahu further said, for decades, cybersecurity has focused on protecting systems. The next decade will be defined by protecting trust. Trust cannot be encrypted by technology alone; it must be engineered through transparency, accountability and intelligent governance. Faceoff Privacy is an important step toward that future, where Artificial Intelligence becomes a Privacy Intelligence System capable of understanding risk before regulators discover it and before adversaries exploit it. In the age of AI, organizations will not be remembered for the amount of data they possess, but for the confidence with which they can justify every byte they retain.

A Unified Platform for Privacy Operations

Faceoff Privacy brings seven core privacy-management capabilities together within one platform:

1. Consent Management

Enables organizations to capture specific, informed and purpose-based consent across websites, mobile applications, APIs and enterprise systems. Consent decisions can be timestamped, versioned and maintained as auditable records. The platform is also designed to communicate consent changes and withdrawals to integrated downstream systems.

2. Privacy Impact Assessment

Helps organizations identify privacy risks associated with new products, business processes, technologies, artificial-intelligence systems and third-party integrations. It supports structured assessments, risk scoring, mitigation planning, stakeholder reviews and approval workflows.

3. Data Principal Access Request Management

Manages requests involving access to personal data, correction, completion, updating, erasure and grievance resolution—from intake and identity verification through internal fulfilment and documented closure. The module includes workflow routing, service-level tracking, evidence management and searchable case histories.

4. Confidential Data Discovery

Scans databases, file repositories, cloud environments and enterprise applications to identify and classify personal and confidential information. It helps privacy and security teams understand what data the organization holds, where it is located, which systems process it, how it moves and whether it is adequately protected.

5. Data Breach Management

Supports the complete incident lifecycle—from initial identification and triage through impact assessment, internal escalation, notification preparation, evidence collection and closure. Automated workflows and deadline tracking help organizations manage applicable personal-data-breach notification requirements.

6. Privacy Gap Assessment

Maps an organization’s policies, controls, processes and technical safeguards against applicable DPDPA obligations. The platform maintains an evolving view of the organization’s compliance posture, including identified gaps, assigned owners, remediation priorities, target dates and supporting evidence.

7. Compliance Audit Management

Centralizes evidence generated across the privacy program, including consent records, Data Principal request case files, breach documentation, privacy impact assessments, remediation records and system activity logs. This creates a searchable audit trail for internal reviews, management reporting and regulatory inquiries.

AI-Powered and Designed for Indian Enterprises

Faceoff Privacy has been built as an India-focused privacy platform rather than as an international compliance product retrofitted with an additional DPDPA module. The platform is designed around India’s regulatory environment, enterprise architecture patterns, linguistic diversity and data-sovereignty requirements.

Responsible AI Architecture

At the core of the platform is Faceoff Technologies’ proprietary Adoptive Cognitive Engine, or ACE, which applies artificial intelligence to privacy discovery, data classification, risk identification, control mapping and compliance analysis.

On-Premises Small Language Models

Faceoff Privacy can use Small Language Models deployed within the customer’s controlled environment. This allows organizations to apply AI-assisted privacy capabilities without sending sensitive enterprise data to externally hosted public AI systems.

Privacy-Preserving AI

The platform supports privacy-enhancing techniques such as tokenisation and differential privacy. These capabilities can help organizations use personal-data-derived insights while reducing unnecessary exposure of identifiable information.

Advanced Cryptographic Protection

Faceoff Privacy is designed to support integration with Hardware Security Modules and advanced cryptographic controls, including post-quantum-ready security architectures.

Flexible and Sovereign Deployment

The platform supports managed and customer-controlled deployment models, including fully on-premises implementation. This is especially relevant for enterprises with strict data-residency, sovereignty or sectoral-security requirements.

The DPDPA Implementation Timeline

The Government of India notified the phased commencement of the DPDP Act and the Digital Personal Data Protection Rules in November 2025.

Phase	Effective date	Regulatory position	Enterprise priority
Phase 1	November 2025	Specified institutional, rule-making and Data Protection Board-related provisions commenced	Establish governance, accountability and implementation programs
Phase 2	November 2026	Consent Manager-related provisions commence	Prepare registration, interoperability and governance capabilities where applicable
Phase 3	May 2027	Most substantive obligations under the Act and Rules commence	Operationalize notices, consent, rights management, security safeguards, breach response, erasure and parental consent

Organizations should treat May 2027 as an implementation deadline—not as the point at which implementation planning should begin. Privacy transformation frequently requires changes across websites, applications, customer databases, marketing platforms, identity systems, data warehouses, artificial-intelligence platforms and third-party integrations.

Making Compliance Demonstrable

The DPDPA requires organizations to move beyond privacy policies and establish operational controls supported by evidence. A mature privacy-management program should be capable of demonstrating that:

• Consent was specific, informed and associated with a defined purpose.
• Consent withdrawals were implemented through relevant processing systems.
• Data Principal requests were received, verified, processed and documented.
• Personal data was erased when the purpose was completed and retention was no longer legally required.
• Reasonable security safeguards were applied to protect personal data.
• Personal-data breaches were identified, assessed, escalated and notified as required.
• Parental consent was verifiably obtained before processing children’s personal data, subject to applicable exemptions.
• Privacy risks associated with processors, third parties and AI systems were assessed and managed.

Faceoff Privacy is designed to maintain this evidence as part of everyday privacy operations rather than recreate it only when an audit or regulatory inquiry occurs.

Industries That Can Benefit

• Banking, financial services and insurance: Banks, NBFCs, insurers, payment companies and cooperative financial institutions
• Healthcare and life sciences: Hospitals, diagnostics providers, telemedicine companies and pharmaceutical organizations
• Fintech: Lending, wealth-management, payment and insurance-aggregation platforms
• E-commerce and retail: Marketplaces, direct-to-consumer businesses and loyalty-program operators
• Education technology: Platforms handling student information, parental consent and learning analytics
• Manufacturing and supply chain: Organizations managing employee, vendor and customer data across complex operational environments
• Government and public-sector enterprises: Agencies and institutions processing citizen and beneficiary information
• AI-enabled enterprises: Organizations using personal data to train, configure, operate or evaluate artificial-intelligence systems

Demonstration and Readiness Assessment

Faceoff Technologies is offering organizations an opportunity to evaluate their DPDPA readiness through:

• A live demonstration of the seven integrated modules
• A DPDPA obligation-to-platform capability mapping
• An architecture review for SaaS, private-cloud or on-premises deployment
• A personalized privacy gap assessment
• An implementation-readiness and integration workshop
  
  

“India should not have to depend exclusively on foreign privacy infrastructure to protect Indian personal data. Faceoff Privacy represents our commitment to building responsible, secure and enterprise-grade privacy technology in India for Indian organizations.” — Dr. Deepak Kumar Sahu

About Faceoff Technologies

Faceoff Technologies is an Indian deep-technology company focused on artificial intelligence, privacy engineering, confidential-data protection and regulatory technology. The company develops enterprise platforms that help organizations discover and protect confidential information, manage privacy operations, apply responsible AI and maintain demonstrable regulatory compliance.

Faceoff Privacy is the company’s Unified Privacy Management Platform for operationalizing privacy governance, consent, Data Principal rights, confidential-data discovery, breach response and compliance assurance.