- Overview
- Products
- Industries
- Services
Empowering You Through Digital Transformation
We share news, insights, analysis and research – tailored to your unique interests – to help you deepen your knowledge and impact.
Data privacy has moved from compliance checkbox to boardroom priority. As businesses digitize and adopt AI across functions—from content creation and research to coding and analytics—the risk surface expands dramatically. Employees now rely on tools like ChatGPT, Copilot, Bard, Claude, and internal LLMs to speed up work. Productivity soars—but so do privacy risks, especially when sensitive information finds its way into AI prompts or browser-based workflows.
Two regulatory pillars define modern privacy expectations: India’s Digital Personal Data Protection (DPDP) Act and Europe’s General Data Protection Regulation (GDPR). While they differ in origin and scope, both share the same core expectation: protect personal data rigorously, prove accountability continuously, and prevent unauthorized disclosure—by design
Traditional security stacks—built for emails, endpoints, and file transfers—weren’t designed to understand prompts, inspect browser interactions, or monitor AI usage in real time. That’s the gap Quadrafort set out to close. Its AI-native Q‑DLP (Data Loss Prevention) platform brings visibility, policy enforcement, and auditability to the exact places where modern risk begins: prompts, browsers, endpoints, and AI tools.
This blog breaks down DPDP and GDPR, the AI risk landscape, why legacy tools struggle, and how Quadrafort’s Q‑DLP helps organizations stay compliant—without slowing innovation.
The DPDP Act frames personal data protection around a simple idea: your data is yours. Organizations (termed Data Fiduciaries) are custodians who must process data lawfully, transparently, and with purpose limitation. Key expectations include:
AI adoption complicates these duties. A single prompt containing customer identifiers, financial data, or source code pasted into an external AI tool can constitute exposure. Shadow AI—unapproved tools used informally by teams—widens blind spots.
Quadrafort’s Q‑DLP operationalizes DPDP requirements by:
Since 2018, GDPR has set the global standard for privacy. Its foundations—lawfulness, fairness, transparency, integrity, confidentiality, storage limitation, and accountability—grant individuals rights to access, rectify, erase, port, and object to processing. For organizations, GDPR demands not only secure processing but proof of secure processing.
The stakes are high: penalties can reach €20 million or 4% of global annual turnover, whichever is higher. Cross-border transfers, consent records, technical and organizational measures (TOMs), and privacy by design and by default (Article 25) are non-negotiable.
Generative AI changes how people work—and how data moves:
Employees paste sensitive snippets—from CRMs, spreadsheets, tickets, repos—into AI tools without considering storage or processing locations.
Many AI systems operate in external clouds. This triggers GDPR cross-border considerations and DPDP fiduciary responsibilities.
Teams adopt unapproved tools to move faster. Security and compliance teams lose visibility and control.
Traditional solutions can’t see what’s typed in prompts, nor can they apply real-time policy checks inside the browser.
The “copy→paste→prompt” pattern is common. Without endpoint intelligence, organizations learn about exposure only after it happens.
Net result: Organizations need AI-aware protection, not retrofitted controls.
Legacy DLP was built for emails, file transfers, USB, and network perimeters. Today’s risks happen in browsers and AI apps:
Quadrafort didn’t retrofit a legacy DLP—it engineered Q‑DLP for the AI era. Four layers deliver end-to-end protection:
Intercepts prompts in real time. Detects and blocks sensitive content before submission across ChatGPT, Copilot, Bard, Claude, and internal LLMs.
Monitors clipboard, keystroke patterns, app activity, and outbound connections—catching exposure upstream of the browser. Designed to preserve employee privacy (no raw keystroke storage) while preventing risky pastes
A single pane for visibility, policies, incident response, and analytics. Role-based access controls help compliance and InfoSec teams govern usage at user, team, and department levels.
Goes beyond regex with contextual intelligence to identify PII/PHI, credentials, tokens, source code, financial data, and proprietary content. Severity tiers (Critical/High/Medium/Low) cut false positives and streamline triage.
Philosophy: Maximum protection, minimal friction. Q‑DLP runs silently, enabling safe AI use without slowing teams down.
Regulations demand continuous protection, not ad-hoc audits. Q‑DLP brings compliance into daily workflows:
into browser and endpoint actions.
aligned with minimization, purpose limitation, and consent models.
that capture prompt text, screenshots (where configured), user justifications, triggers, and metadata.
via role-based controls, team-level policies, and instant alerts.
for GDPR/DPDP-aligned rules so teams can deploy in days.
This approach turns compliance from a project into a capability.
The most transformative capability is pre-submission inspection. Instead of discovering breaches after transmission, Q‑DLP stops unauthorized sharing at the source:
as users type in browser or supported apps.
of identifiers (e.g., PAN-like formats), credentials, tokens, clinical or financial terms, and code fragments.
Employees see clear alerts. When legitimate business need exists (e.g., testing), they can add justifications—creating an audit trail without crippling productivity.
Consistent policies across major AI tools and developer environments (e.g., Copilot in IDEs).
Lightweight enforcement avoids lag or user friction
This is privacy by design, aligning with GDPR Article 25 and DPDP’s proactive fiduciary responsibility.
AI usage isn’t only web-based. Emails, desktop apps, terminals, and IDEs all intersect with AI:
Areas of Focus:
Together, these controls prevent leakage regardless of channel—supporting DPDP and GDPR mandates to safeguard data end-to-end.
Regex-only systems struggle with nuance. Quadrafort’s detection engine applies context-aware intelligence to reduce noise and elevate signal:
PII, PHI, auth credentials, tokens/keys, payment details, source code, financial and proprietary info.
Severity scoring sharpens triage and escalations.
Policies can be tuned per department (e.g., dev, finance, HR) to reflect real data needs while maintaining guardrails.
Result: fewer false positives, faster response, better user experience.
Compliance teams need clarity:
for AI usage, violations, patterns, and trends.
with escalation, assignment, and resolution tracking.
to separate duties (e.g., InfoSec vs. Legal).
aligned to DPDP/GDPR expectations.
for audits, board updates, and regulator inquiries.
This is audit-readiness on tap —no more stitching logs from scattered systems.
Security tools fail when they slow teams down. Q‑DLP is built to deploy fast and scale smoothly:
cloud, on‑prem, or hybrid.
start with visibility mode, then enable blocking in high-risk areas.
tailor rules to dev, finance, HR, legal, and support.
user-friendly prompts and warnings educate employees in the flow of work.
surface unapproved tools to inform governance decisions.
Within days, organizations move from blind spots to controlled, compliant AI adoption
Scenario: A developer pastes API keys and internal code into a Copilot-enabled IDE for debugging
Outcome: No leakage, clear accountability, continuous improvement.
Quadrafort helps privacy and security become growth enablers:
and potential fines under DPDP/GDPR.
with demonstrable safeguards.
safely across teams.
with central visibility and audit-ready logs.
turning guardrails into everyday habits.
DPDP and GDPR redefine how organizations must treat personal and sensitive data. The rise of AI adds a layer of complexity that legacy tools can’t handle. The answer isn’t to block AI—it’s to adopt AI safely, with controls that understand prompts, browsers, endpoints, and real workflows
Quadrafort’s Q‑DL delivers exactly that. With real‑time prompt inspection, endpoint intelligence, context-aware detection, and governance built-in, it enables privacy by design and compliance by default—without disrupting how people work
In a world where a single prompt can trigger a regulatory incident, Quadrafort ensures privacy, security, and productivity move in lockstep. That’s how modern enterprises stay compliant—and future-ready.
