Secure AI at Enterprise Scale—From Training Data to Model Access

AI initiatives accelerate business value but introduce new risks: sensitive data exposure, compliance blind spots, and uncontrolled model access. Kontxtual for AI Security gives enterprises the visibility and policy control needed to protect AI workflows—without slowing innovation.

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AI Changes the Risk Surface—Traditional Tools Can’t Keep Up

Traditional security and DLP tools weren’t built for the dynamic, distributed nature of AI workflows. Sensitive data flows into training sets unnoticed. Model outputs may expose proprietary or regulated information. And access controls fail to differentiate between human users and machine identities. The result? Blind spots, regulatory exposure, and models that can’t be trusted.

AI requires protection that’s contextual, continuous, and built for scale.

See Where Gaps Exist in Your AI Security Posture

Purpose-Built AI Security that Understands Both Data and Models

Kontxtual for AI Security provides contextual protection across your AI lifecycle. By connecting data, identity, usage, and risk in near real time, it enables proactive enforcement and visibility from source to model output—so enterprises can scale AI responsibly.

What sets Kontxtual apart:

AI-Aware Context: Understands the purpose, owner, and regulatory profile of training data.
Unified Governance: Extends DSPM, access intelligence, and policy enforcement directly into AI workflows.
Enterprise-Scale Architecture: Handles petabyte-scale, hybrid, cloud, and federated environments without performance trade-offs.
Holistic, consistent data labeling: Leverage semantic views to apply metadata tags to files on-prem or cloud without impacting Last Accessed, Last Modified, or Date Created fields
Contextualized scanning: Easily view production data in non-production environments to ensure developers are working with anonymized data
Continuous Discovery & Enforcement: Scans data at rest and in motion, applying real-time, identity-aware policies at the data layer.
Seamless Integration: Works natively with Snowflake, Databricks, BigQuery, Guardium, and Data tools to fit within your existing stack.
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Precision Control Across the AI Lifecycle

Kontxtual for AI Security combines discovery, protection, and enforcement to secure data across every phase of AI—from ingestion to inference. Each capability is purpose-built to protect AI pipelines from exposure, drift, or misuse—without slowing innovation.

Capability
What it Does
Why it Matters
Sensitive Data Discovery
Contextual Classification
AI-Aware Policy Engine
Access Intelligence
Governance
Data-in-Motion Protection
DLP for AI Training
LLM-Based Classification
MSPM (Mainframe Protection)
Continuously scans structured and unstructured data across environments before it enters AI pipelines.
Applies multi-dimensional classification with regulatory and business context.
Enforces guardrails on data movement, model training,
Identifies and governs both human and machine identities accessing AI data.
Applies policies for usage control, tagging, retention, and ownership.
Detects and classifies sensitive data in transit across your infrastructure.
Flags, blocks, or quarantines high-risk data from entering training sets.
Uses AI-assisted analysis to enhance detection of complex or contextual content.
Extends AI security to mainframe data sources (e.g., VSAM, Db2 on Z).
Prevents sensitive or non-compliant data from being used in training
Flags risks based on context and purpose, not just keywords or formats.
Ensures AI development and deployment remain compliant, auditable, and controlled.
Prevents privilege sprawl, insider misuse, and uncontrolled service accounts.
Ensures that data used in AI meets internal standards and external regulations.
Prevents unintentional exposure in real-time without disrupting operations.
Ensures responsible AI use and prevents memorization of sensitive content.
Improves precision and recall, especially in unstructured training datasets.
Enables comprehensive protection in hybrid and legacy environments.
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Business Value That Extends Beyond Compliance

Kontxtual for AI Security enables organizations to innovate with confidence by aligning AI development with security and governance requirements.

Protect Training Data Proactively: Ensure sensitive or regulated data never enters AI models.
Control Human and Machine Access: Manage entitlements across developers, data scientists, and automated processes.
Control Human and Machine Access: Manage entitlements across developers, data scientists, and automated processes.
Enable Trusted AI Innovation: Give business units and regulators confidence in AI initiatives at scale.
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Extend Your AI Security Posture

Strengthen your protection based on your regulatory requirements and AI initiatives. These modular add-ons extend Kontxtual’s reach across high-risk environments:

LLM-Based Classification
What it Does: Boost detection accuracy with AI-assisted classification models for unstructured or novel data types.

Why it Matters: Ideal for GenAI and NLP use cases.
Network Analytic Engine
What it Does: Capture and classify network traffic to enforce policies across HTTP, SQL, and SMB protocols—without disrupting traffic.

Why it Matters: Prevents leakage before it enters your AI pipelines.
Extend your protection in high-risk or hard-to-reach environments.
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Power the Workflows That Drive Risk Reduction and Readiness

Get clarity on who has access to what sensitive data—and why. Kontxtual Access Intelligence supports the day-to-day workflows your teams rely on to reduce exposure, pass audits, and move faster with confidence.

Third-Party Risk Management
What you get: Continuous visibility into external identities and their access to sensitive data.
Outcome: Reduce vendor risk by identifying and removing unnecessary or excessive third-party access.
Third-Party Risk Management
What you get: Continuous visibility into external identities and their access to sensitive data.
Outcome: Reduce vendor risk by identifying and removing unnecessary or excessive third-party access.
Third-Party Risk Management
What you get: Continuous visibility into external identities and their access to sensitive data.
Outcome: Reduce vendor risk by identifying and removing unnecessary or excessive third-party access.
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Proven Results in Enterprise AI Environments

Trusted by global leaders to govern sensitive training data.

Fortune 100 Financial Services Leader

Faced with growing AI compliance pressure, this enterprise used Kontxtual to vet data flowing into Snowflake, Databricks, and BigQuery. Sensitive fields were flagged and removed before ingestion—securing compliant model training and reducing audit risk

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Where AI Security Fits in Your Data Maturity Journey

As enterprises scale AI, safeguarding training and inference data is critical for compliance, trust, and operational control. Kontxtual for AI Security moves organizations from Stage 3: Automated Governance to Stage 5: Federated Data Management on the Kontxtual Maturity Map—providing the oversight needed to run AI safely at enterprise scale.

With Kontxtual, organizations gain:
Centralized governance of AI data across hybrid and multi-cloud pipelines
Policy-driven enforcement aligned to regulatory and business risk requirements
Continuous monitoring and explainability for audit, compliance, and trust
Cross-team visibility so security, legal, and data science move in lockstep
Talk to an expert about automating your data classification workflows.
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Explore the Kontxtual Maturity Map

Secure AI with Confidence

AI presents enormous opportunities—but also introduces new risks around data, compliance, and trust. Kontxtual for AI Security gives enterprises the visibility and control to manage those risks from day one. Whether piloting a single model or scaling AI across the business, Kontxtual provides the guardrails to innovate securely, responsibly, and at enterprise scale.
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