By Use Case

Unlock Privacy-Centric
Innovation at Scale

From Consent to Clean Rooms—Real-World Use Cases That Power Responsible AI, Data, and Growth

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At PrivaSapien, every use case is born from real-world customer challenges—where privacy isn’t just a checkbox, but a core enabler of innovation. From navigating consent in dynamic ecosystems to deploying AI responsibly, these use cases showcase how our solutions are solving mission-critical problems across industries. Whether it’s mitigating regulatory risk, unlocking safe data collaboration, or de-risking GenAI adoption, these aren’t hypothetical scenarios—they’re proof points. Explore how privacy-centric technology transforms bottlenecks into breakthroughs—securely, ethically, and at scale.

01

Manage your Consent
A Consent Solution that is Provable, Verifiable, Withdrawable and Multilingual in Current State of Consent Management
The Problem

Checkbox Consent Isn’t
Real Consent Anymore 

Without an active, transparent, and revocable consent layer, businesses risk regulatory violations, broken user trust, and massive fines.
No Legal Proof of Consent
Not auditable or legally provable in case of scrutiny.
Disconnected from Data Flows
Siloed—not linked to actual data flows or RoPA, DPIA, or DSR processes.
No Multilingual or Regional Support
Lacking multilingual and region-specific adaptation.
Fails GDPR/DPDP Compliance
Non-compliant with GDPR/DPDP mandates for “freely given, specific, informed” consent.
No Consent Revocation or Traceability
Fail to manage revocation, reuse, or downstream visibility
The Solution

Consent That Flows with Your Data  

Consentium delivers a next-generation consent experience—one that is digitally signed, auditable, user-controlled, and deeply integrated with your privacy stack.

What Consentium Delivers!

Linked to Real Data Flows
Consent lives with the data, not separate from it
Digitally Signed & Legally Verifiable
Proof-ready logs for every consent or withdrawal action
Fully Withdrawable & Traceable
Let users revoke consent and trace how their data was used
Multilingual & Region-Specific Customization
Meet global legal expectations with localized flexibility
Integrated with RoPA, DPIA, and DSR
Auto-align consent records with your core governance systems
Transparent Data Request & Processing Logs
Let users revoke consent and trace how their data was used
Grievance Redressal & Compliance Assurance
Empower users to report violations and ensure lawful data use
Seamless UX with User-Centric Control
Offer frictionless yet powerful control over personal data

Consentium transforms passive checkboxes into active, enforceable, privacy-proof agreements—boosting compliance, trust, and operational agility. 

02

Manage your cookie preference
How to Manage Your Cookie Preferences - Compliantly and Transparently
The Problem

Static Cookie Banners Are No Longer Enough

Most websites still rely on static cookie banners that display generic opt-in prompts but don’t enforce user preferences—leaving businesses exposed to legal and reputational risks.
Broken Consent Mechanisms
Non-functional banners that ignore user choice or pre-load trackers
Risk of Massive Fines
Massive fines for cookie misuse (e.g., €100M+ fines to Google/Facebook)
No Regional Compliance
Lack of region-specific behaviour across global markets (EU, India, CCPA)
No Multilingual Support
No multilingual support, damaging accessibility and inclusivity
No Traceability or Logs
No audit trail or enforcement logs
Disconnected from Core Privacy Ops
Disconnected from RoPA, DSR, or broader privacy operations

Without a dynamic, enforceable cookie system, organizations risk breaching GDPR, ePrivacy, and upcoming DPDP requirements—even with good intentions.

The Solution

Real-Time, Region-Aware Cookie Governance

Privasapien’s Cookie Management goes far beyond popups. It's a compliance-grade system that not only collects consent—but enforces it intelligently, in real time.

What Our Cookie Management Solution Delivers!

Automatic Cookie Discovery & Dynamic Classification
Scans each site/app to detect and categorize cookies by type, purpose, and risk
Plug-and-Play SDKs and CDN Enforcement
Control cookie behaviour with minimal integration effort across your tech stack
Real-Time Preference Enforcement
Block or allow cookies based on actual user choices—not pre-set defaults
Region-Aware & Multilingual Behavior
Automatically adapts banner logic and disclosures based on location laws (EU, India, US, etc.)
Digitally Signed Consent Logs
Create tamper-proof, audit-ready records for every user interaction
Seamless Integration with RoPA, DSR & Privacy Governance
Connect cookie actions with user rights workflows and your privacy compliance tools

Stop worrying about cookie compliance. With Privasapien, your cookie collection becomes transparent, enforceable, user-friendly, and globally compliant.

03

Govern your privacy with DPIA
Effortless Privacy Governance at Scale – Automate DPIA to De-Risk, Accelerate, and Comply.
The Problem

Traditional DPIAs Are Outdated and Inefficient

Privacy Impact Assessments (DPIAs) are a regulatory must under GDPR Article 35, India DPDP, and other global laws. But today’s DPIAs are often
Outdated Compliance Artifacts
Static, checklist-based documents disconnected from real workflows
Slows Down Delivery
Time-consuming, delaying innovation and releases
Not Built to Scale
Hard to scale across regions, business units, or high-frequency data flows
Blind to Emerging Risks
Blind to modern data risks like AI model exposure or shadow IT

Result? Privacy teams struggle to keep up, while businesses face non-compliance, project delays, and avoidable risks.

The Solution

DPIAs That Think, Adapt, and Scale

Privasapien’s DPIA solution brings together Agent Plato for automation and context awareness, and Prescriptron for deep policy and risk alignment. Together, they make DPIAs smarter, faster, and audit ready.

What the Agent plato and Prescriptron Offers!

Adaptive DPIA Engine (Agent Plato)
Dynamic DPIAs that evolve in real time based on region, data sensitivity, purpose, and regulatory scope.
Consent Lifecycle Orchestration
Automate consent collection, withdrawal, and tracking across web, mobile, and API layers.
Legal Compliance Alignment
Ensure all DPIA outputs are aligned with GDPR, DPDP, CCPA, and other key regulations.
RoPA-Integrated Workflow Automation
Use your existing Record of Processing Activities (RoPA) to drive DPIA triggers and task flows.
Cross-Border Compliance Support
Identify risks tied to international data transfers and automate policy-driven remediation.
Proactive Risk Intelligence (Prescriptron)
Spot hidden privacy risks early using a privacy risk scoring engine built for evolving data ecosystems.

From risk discovery to policy enforcement, Agent Plato + Prescriptron give you a seamless, intelligent, and regulation-ready DPIA process that supports innovation while safeguarding compliance.

04

Visualize your privacy risk flows with RoPA
Visualize Your Privacy Risks in Real-Time
The Problem

Current risk faced

In modern businesses, personal data flows across countless apps, vendors, and cloud systems—but most organizations can’t clearly see where it’s going or why. Privacy teams still rely on manual spreadsheets to maintain their RoPA (Record of Processing Activities), which quickly becomes outdated and disconnected from real data flows. This leaves you:
No Visibility into Data Flows
Blind to unauthorized data transfers
Risky Collection & Sharing
Unaware of overcollection or risky sharing
Unready for Incidents & Oversight
Unprepared for audits, breaches, or cross-border issues

Without real-time visibility, you’re left exposed to regulatory fines, reputational damage, and compliance gaps.

The Solution

RoPA Visualization Powered by Privacy X-Ray + Nebula

RoPA is more than a compliance requirement—it’s your organization’s data blueprint.

What we do!

Privacy X-Ray: Real-Time Data Flow Mapping
Privacy X-Ray continuously maps structured data processing activities—across SaaS apps, databases, and APIs—highlighting how personal data moves between systems, departments, and vendors. It auto-generates a live, interactive RoPA—making privacy operations visible, actionable, and compliant.
Nebula: Discovery for Unstructured Data
Meanwhile, Nebula augments this map by scanning unstructured data sources like file shares, logs, emails, and dev environments—identifying hidden data flows and undocumented processing activities that most systems miss.
360° Privacy Risk Visibility
Together, they provide a 360° view of your privacy risk landscape, ensuring your RoPA isn’t just compliant—it’s real-time, risk-aware, and regulator-ready.
Govern with Clarity. Act with Insight. Scale with Confidence.
Privacy X-Ray + Nebula gives you the clarity to govern, the insight to act, and the automation to scale.

From risk discovery to policy enforcement, Agent Plato + Prescriptron give you a seamless, intelligent, and regulation-ready DPIA process that supports innovation while safeguarding compliance.

05

Your Privacy Risks Are Hiding in Plain Sight
Why Traditional Tools Aren’t Enough Anymore
The Problem

Modern businesses are sitting on a ticking privacy time bomb.

From cloud folders and backups to forgotten logs, codebases, and spreadsheets—PII and sensitive personal data are scattered across your ecosystem, far beyond structured systems. Most tools only skim the surface. And manual audits? They’re outdated, error-prone, and slow.
Blind Spots Everywhere
Traditional DLPs miss inferred identifiers, derived personal data, and unstructured file types like emails, contracts, and screenshots.
No Unified View of Risk
Fragmented visibility between your databases, dev environments, CRMs, cloud shares, and third-party tools leaves you exposed.
Compliance Nightmares
Whether it’s GDPR, DPDP, HIPAA, or CCPA—regulators demand accurate, auditable proof of where sensitive data lives and how it’s used.
The Solution

Uncover Hidden PII and Risk Hotspots Across Your Data Estate

Knowing what personal data you hold—and where—is the first step in any privacy program.

What we Deliver!

Deep Scanning of Unstructured Data
Nebula dives deep into your unstructured data: documents, emails, backups, source code, and logs—detecting PII/SPI using transformer-based models, classifying file types, and tagging risky artifacts. It supports customizable scan rules, enabling you to tailor privacy scanning to your specific business policies and risk thresholds.
Visibility into Structured Systems
Privacy X-Ray complements this by scanning structured environments like databases, CRMs, and APIs to identify high-risk zones—such as overcollection, sensitive data clusters, and legacy retention violations.

The result? A prioritized inventory of privacy risks across all data types, giving your teams the insights they need to clean up risk, enforce policies, and avoid penalties.

06

Quantify risk in data requests for regulation
The Problem

Data requests are approved ad hoc—without measuring regulatory risk. DPOs struggle to quantify privacy impact, especially in fast-paced data teams.

The Solution

Score Every Data Request. Make Privacy-by-Design Real.

Approving or denying data access shouldn’t rely on guesswork!

Inconsistent Privacy Risk Scoring Slows Decisions
No standardized way to quantify privacy risks across data sensitivity, purpose, and global jurisdictions.
Blind Spots in Unstructured Data Pose Hidden Threats
Critical risks in emails, logs, codebases, or shared drives go undetected by traditional tools.3. DPIA Approvals Lack Auditability and Real-Time Tracking
DPIA Approvals Lack Auditability and Real-Time Tracking
Privacy teams can’t easily log, explain, or verify DPIA decisions when audits arrive.
Privacy-by-Design Is Fragmented Across Business Units
No consistent enforcement of privacy best practices across departments, tools, and workflows.
DPOs Lack Tools to Act Quickly and Confidently
Manual reviews delay approvals and introduce risk, especially when regulations evolve rapidly.

Together, these tools ensure that every request is evaluated holistically, risks are flagged early, and privacy-by-design becomes operational, not optional.

07

Exemption grade anonymization
The Problem

Your “Anonymized” Data May Not Be Compliant

Today’s businesses increasingly share, analyse, and train models on data assumed to be anonymized. But regulators are catching up—and so are re-identifi -cation techniques. Outdated methods like masking, tokenization, or static generalization no longer meet the legal threshold for anonymization under frame -works like GDPR (Recital 26), India DPDP.What businesses now face
AI Inference Breaks Anonymity
High risk of re-identification through AI inference or third-party data joins
Exemptions Can Disappear Overnight
Loss of regulatory exemptions, turning exempt data into regulated data overnight
False Confidence, Real Consequences
False compliance confidence, leading to under-reported breaches or unlawful processing
Scrutiny, Sanctions & Reputational Risk
Increased audit scrutiny, fines, and reputational risk.If your data can still be linked back to individuals—even probabilistically—it’s not truly anonymous, and it’s not exempt.
The Solution

True Anonymization That Meets Legal Exemptions

Event Horizon work to give you verifiable, regulation-grade anonymization—so you can unlock insights and innovation without risking re-identification or regulatory backlash.

Event Horizon: Make Sensitive Data Usable Again !

Anonymize Sensitive Data—No Code, Full Control
Easily mask PII with visual workflows and contextual oversight, without writing a single line of code.
Built for Your Industry, Region, and Compliance Needs
Automatically adapts to sector-specific regulations, data types, and global privacy frameworks.
Enable Secure Cross-Border Data Collaboration
Share data safely across geographies using embedded Privacy Enhancing Technologies (PETs).
Preserve Insights While Protecting Privacy
Retain business value from anonymized datasets—make decisions without compromising compliance.

From risk discovery to policy enforcement, Agent Plato + Prescriptron give you a seamless, intelligent, and regulation-ready DPIA process that supports innovation while safeguarding compliance.

08

Technical safeguards with Vaulting/ encryption
The Problem

Encryption Alone Isn’t Enough Anymore

Today’s data doesn’t just sit still—it flows through apps, APIs, analytics pipelines, and AI models. And every time encrypted data is decrypted for use, it becomes exposed. Most businesses:
Vulnerable During Use
Only encrypt data at rest or in transit—leaving it vulnerable during use
Insecure Secret Management
Store secrets and credentials insecurely across environments
Hard to Prove Compliance
Struggle to prove compliance with data protection laws like GDPR, DPDP, and HIPAA
No Fine-Grained Access Control
Lack fine-grained controls over who accesses what, when, and why

Without deeper, field-level protection and runtime safeguards, traditional encryption becomes a checkbox—not real security.

The Solution

End-to-End Safeguards with Cryptosphere

Cryptosphere adds precision, control, and intelligence to your encryption strategy—ensuring that your sensitive data stays protected even when it’s in use or in motion.

What Cryptosphere Delivers!

Secure API-Based Decryption
Control decryption workflows via APIs with auditable access logs
Attribute-Level Encryption
Encrypt only the sensitive fields (e.g., SSNs, emails, tokens) for flexible, performance-optimized protection
High-Performance Symmetric Encryption
Ensure fast, scalable, and enterprise-grade encryption without bottlenecks
Smart Masking & Pseudonymization
Mask or pseudonymize data while preserving utility—ideal for testing, analytics, and sharing
Compliant, Privacy-Preserved Data Sharing
Enable privacy-preserved data access for internal teams or external partners, with transformations that retain analytical value

Your data is protected at every level—field, record, system, and API—so you can confidently share, analyze, and scale without risk or regulatory gaps.

09

Synthetic data for Model training/ sharing
The Problem

Real Data Is a Risk—Even in AI Training

As AI adoption accelerates, businesses need massive datasets to train models, test pipelines, and build LLM applications. But using real customer or user data introduces major challenges:
Regulatory Risk & Legal Exposure
Privacy violations and legal exposure under GDPR, DPDP, HIPAA, etc.
AI Output Leakage
Sensitive information leakage in AI model outputs (e.g., names, emails, PHI)
Blocked Collaboration
Barriers to data sharing across teams, partners, or geographies
No Safe Way to Experiment
Lack fine-grained controls over who accesses what, when, and why

Using real data in model training or analytics today is a high-stakes liability.

The Solution

Safe, Smart, Synthetic Data with CloneLM

CloneLM generates privacy-preserving synthetic datasets that are statistically accurate, context-aware, and ready for high-quality model training—without exposing real user data.

What CloneLM Delivers!

Context-Aware & Statistically Faithful Generation
Mirrors real data distributions and relationships, tailored to your domain
Built-in Privacy Preservation
Protects identities using differential privacy, k-anonymity, and PETs—ensuring legal compliance
Seamless Integration
Easily plugs into your existing ML pipelines via APIs or connectors, no reengineering needed
Quality-Assured Synthetic Outputs
Rigorous validation ensures synthetic data performs reliably in training and evaluation
Risk-Free Experimentation
Safely share and test data across teams, vendors, or jurisdictions—without exposing real users

CloneLM lets you innovate, collaborate, and scale AI—all while keeping real data private, secure, and out of the equation.

10

Test Data for Application development
The Problem

Using Real Data in Testing Is a Silent Compliance Risk

Developers and QA teams need realistic data to build and test modern applications. But pulling copies of production data into dev, staging, or test environments introduces critical security and compliance risks
Sensitive Data in Unsafe Environments
Real PII or sensitive data often lands in non-secure environments
Regulations Ban Unmasked Test Data
Regulations like GDPR, DPDP, and HIPAA prohibit unmasked test data usage
Test Data Gaps Slow Agile Teams
Developers lack quality test data, slowing down agile delivery
Manual Masking Is Risky and Weak
Manual data scrambling or masking is error-prone and easily reversible. Using real data for testing puts your entire pipeline at legal and reputational risk—and slows innovation.
The Solution

Safe, Smart Test Data with DataTwin

DataTwin generates privacy-preserving, synthetic test data that mirrors real-world structures—without exposing any real user data.

What DataTwin Delivers!

Multi-Table Synthetic Data Generation
Maintain referential integrity across relational databases with intelligent key mapping
Custom Rules + Auto Schema Learning
Generate domain-specific test data by learning from real schemas and applying business logic
Privacy-Safe Non-Prod Environments
Power dev, QA, and staging with safe, compliant synthetic data—no sensitive exposure
Eliminate Regulatory Risk
Test freely without violating GDPR, DPDP, or customer trust
Enable Agile & Secure Experimentation
Ship faster and safer with synthetic test data that mimics production behaviour

DataTwin lets your teams build, test, and release applications faster—without ever risking real data.

11

Data Clean Rooms & Private Insights
The Problem

Data Collaboration Without Privacy Is a Breach Waiting to Happen

Businesses increasingly need to share and analyze sensitive data across teams, partners, or geographies. But traditional sharing approaches put them at risk:
Sensitive Data in Unsafe Environments
Real PII or sensitive data often lands in non-secure environments
Non-Compliance with Privacy Laws
Non-compliance with privacy laws like GDPR, DPDP, HIPAA
Erosion of User Trust
Loss of user trust due to poor data transparency
Barriers to Secure Global Collaboration
Inability to collaborate securely across silos or international borders

Result? Valuable data stays locked, insights are delayed, and collaboration is compromised.

The Solution

Privacy-First Analytics with Data Clean Rooms

Differential Insight creates a secure, privacy-enhanced environment for collaborative analytics—no raw data exposure, no compliance guesswork.

What the Clean Room + Insight Solution Offers!

Differential Privacy for Confidential Insights
Query sensitive datasets with built-in differential privacy that protects identities while preserving analytical accuracy.
SQL Extensions with Parameterized Privacy
Use familiar SQL enhanced with privacy controls like calibrated noise and query constraints.
Fast, Secure, and Governed Analytics
Run real-time analytics with enterprise-grade encryption and data governance.
No Raw Data Movement
Analyze where the data lives—never move, duplicate, or expose it.
Privacy Budget Management
Track and manage how much data is exposed per query with privacy budgeting tools.
Compliance-Driven Data Access
Ensure every query and insight meets GDPR, DPDP, and other privacy regulations with built-in policy enforcement.
Policy-Based Access Controls & Audit
Control who can ask what, when, and how with full logs and audit readiness.

  • Differential Insight empowers you to derive high-value insights without compromising on privacy, user trust, or regulatory compliance.

  • Perfect for secure B2B data collaboration, partner analytics, federated learning, and privacy-safe innovation.

12

Know Your AI Risk
The Problem

You Can’t Govern What You Can’t See

As organizations rapidly adopt AI and LLMs, they face increasing regulatory and reputational risks—often without knowing where those risks lie. Modern AI systems:
Ingest Sensitive & Regulated Data
Ingest massive volumes of sensitive or regulated data (PII, PHI, IP)
Unpredictable & Leaky Outputs
Generate unpredictable outputs that may leak personal or confidential information
Opaque Training & Retention
Lack transparency in training data sources, model behaviour, and retention policies
Outside Compliance Boundaries
Operate outside of existing risk and compliance frameworks

Result? Businesses are exposed to AI hallucinations, model misuse, privacy violations, and legal non-compliance—all without visibility or control.

The Solution

AI Risk Governance with Agent Turing

Agent Turing provides real-time visibility, auditability, and risk analysis for your AI and LLM deployments—so you can manage AI like any other critical system.

What Agent Turing Delivers!

AI Asset Discovery & Inventory
Automatically detect, classify, and catalog AI models across your infrastructure—shadow AI included.
Model Risk Profiling
Evaluate AI models against compliance benchmarks (e.g., GDPR, DPDP, NIST AI RMF) to flag high-risk use cases.
Bias, Privacy & Explainability Scoring
Assess models for privacy leakage, bias amplification, fairness issues, and explainability deficits.
LLM Interaction Monitoring
Monitor how models are queried, what data is exposed, and what responses are generated—in real time.
Governance Policy Enforcement
Map each model to your enterprise AI policy and ensure responsible AI practices at scale.
Audit Trails & Accountability
Maintain immutable logs for AI usage, input/output data, and risk flags for every interaction.

  • With Agent Turing, you gain full visibility into your AI landscape and can confidently detect, measure, and mitigate risk—before it turns into a breach or scandal. Make your AI explainable, auditable, and responsible—at enterprise scale.

13

Governance for Your AI Deployments
The Problem

AI at Scale Without Gover-nance Is a Business Risk

As AI rapidly scales across industries, most enterprises lack the tools to govern their deployments. AI models are being pushed into production without proper oversight, policy enforcement, or regulatory . Current challenges customers face:
Shadow AI from Lack of Visibility
No centralized visibility of AI/ML assets across teams, leading to shadow AI
Missing Data Lineage & Consent Records
Lack of documentation on data provenance, consent, and lawful basis of processing
Untracked Drift & Bias Over Time
Inability to track model drift, retraining history, or algorithmic bias over time
Siloed MLOps & Compliance
Disconnected MLOps and compliance workflows, creating fragmented governance
Mounting Global Regulatory Pressure
Rising global pressure from regulations like EU AI Act, India DPDP, NIST AI RMF, and ISO 42001

Result? AI is deployed without a system of accountability, transparency, or risk controls—leaving businesses open to legal exposure, reputational damage, and ethical failures.

The Solution

Full-Spectrum AI Governance with GovernRAI

GovernRAI is a purpose-built platform for governing AI/ML deployments across their lifecycle—from model creation to post-production monitoring.

What GovernRAI delivers!

Centralized AI Model Registry
Discover and track all models across environments, tagging them by purpose, sensitivity, risk score, and business owner.
Data Lineage & Consent Tracing
Document model training data origin, lawful basis (e.g., consent, contract), and jurisdiction-specific requirements.
Drift Detection & Retraining Logs
Monitor concept/data drift and enforce retraining policies with full auditability.
CI/CD & MLOps Integration
Plug into existing ML pipelines to auto-check compliance before deployment.
AI Risk Control Frameworks
Align with AI compliance standards such as EU AI Act risk tiers, NIST AI RMF, and ISO 42001.
Explainability & Fairness Reporting
Generate interpretable model summaries and fairness diagnostics for review and escalation.
Policy Enforcement & Approvals
Apply rules for explainability, privacy, and safety before each deployment stage.
Governance Dashboards & Alerts
Visualize deployment posture, risk events, and governance health in real-time.

  • With GovernRAI, you can confidently scale AI without losing control. Establish trust, accountability, and compliance across your AI lifecycle.

  • Bring structure and safety to your AI strategy—from sandbox to real-world deployment.

14

Privacy & Guardrails for AI, LLMs, and Agentic Systems
The Problem

GenAI and LLMs Are Powerful but Unpredictable

Organizations are deploying GenAI models and LLM-powered agents faster than ever—but most lack the privacy controls and safety checks required to manage the risk
Sensitive Data Leakage via LLMs
Sensitive data leakage via LLM prompts or outputs
Hallucinations & Brand Risk
Hallucinated or non-factual content, leading to misinformation or brand harm
Uncontrolled Agent Behavior
No control over agent behaviour, autonomy, or decision boundaries
Missing Regulatory Guardrails
Lack of guardrails for compliance with GDPR, DPDP, HIPAA, or AI-specific regulations
No Usage Governance or Visibility
Absence of usage governance or visibility into how GenAI is used across the org

Result? Legal exposure, customer trust erosion, ethical lapses, and security breaches due to ungoverned AI usage.

The Solution

RAI FireLM — Real-Time Privacy + Guardrails for AI & GenAI Systems

RAI FireLM is a runtime privacy enforcement and safety policy engine for LLMs and AI agents. It embeds control, traceability, and compliance into every model interaction.

What RAI FireLM Delivers!

LLM Privacy Firewall
Serves as a protective layer between users and models, neutralizing privacy risks and shielding sensitive prompt content.
Robust Model Security
Detects and blocks prompt injection attacks, jailbreaks, and exploits with real-time monitoring and alerting.
Enhanced User Safety
Analyzes prompt intent and suggests privacy-preserving synthetic alternatives, with dynamic query authorization.
Prompt Reversal Protection
Ensures LLM responses reflect genuine user intent, avoiding manipulation or hallucinated redirections.
Usage Intelligence Dashboards
Track GenAI/LLM usage across teams with real-time insights into patterns, anomalies, and risks.
Privacy-First AI Usage Policies
Define enforceable controls for prompt types, redaction, user roles, and compliance needs.
Agent Behavior Constraints
Scope LLM agent functionality with defined roles, guardrails, and limited permissions.
Audit Trails & Logging for Every Interaction
Record complete logs of GenAI usage, enabling investigations, reporting, and regulatory readiness.
Seamless Governance Integration
Connect with your broader privacy and security stack, including RoPA, DSR, DPIA, and consent platforms.

  • With RAI FireLM you can protect privacy, safety security and fairness of AI Model deployment during inference in your ecosystem.

  • Accelerate your Responsible AI Journey for various global AI Regulatory Requirements.

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Arakere Bannerghatta Rd, Omkar Nagar,
Arekere, Bengaluru, Karnataka 560076

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