Nightfall AI

What is Nightfall AI

Nightfall AI is an all-in-one data loss prevention (DLP) platform that uses AI to discover, classify, and protect sensitive data across SaaS apps, generative AI tools, endpoints, and cloud services. It detects PII, PHI, PCI, secrets like API keys, and source code, then automatically alerts, redacts, or blocks to prevent data exfiltration. With data detection and response, data exfiltration prevention, data security posture management, encryption, and an AI firewall for LLMs, Nightfall helps reduce breach risk, improve visibility into data flows, and streamline compliance (e.g., GDPR, HIPAA, SOC 2).

Main Features of Nightfall AI

• AI-powered detection: Accurate classification of PII, PHI, PCI, secrets, and code in structured and unstructured data, including images via OCR.
• Data Detection & Response (DDR): Real-time alerts, triage, risk scoring, and automated remediation workflows (redact, quarantine, revoke sharing).
• Data Exfiltration Prevention: Policy-based blocking for risky sharing, downloads, or copy/paste across SaaS, gen AI apps, and endpoints.
• Data Security Posture Management (DSPM): Inventory and risk assessment of data across cloud and SaaS to remediate misconfigurations and overexposure.
• AI Firewall for LLMs: Inspect and sanitize prompts/responses, mask sensitive content, and enforce guardrails across gen AI tools.
• Encryption & tokenization: Protect sensitive data with masking, hashing, or encryption to minimize exposure and enable safer workflows.
• Broad integrations: Connectors for Slack, Google Drive, GitHub, Jira, Confluence, Notion, email, cloud storage, and SIEM/SOAR tools.
• Custom policies & detectors: Build precise rules, exact data match, regex, and context-aware detection tuned to your environment.
• Developer APIs & SDKs: Embed detection into CI/CD, data pipelines, and applications to prevent secrets and PII leaks earlier.
• Compliance reporting: Evidence and audit-ready reports for GDPR, HIPAA, PCI DSS, SOC 2, and internal governance.

Who Can Use Nightfall AI

Nightfall AI is designed for security and compliance teams, IT administrators, DevSecOps, and data governance leaders who need to protect sensitive data across SaaS and AI tools. Common use cases include safeguarding customer PII in collaboration platforms, preventing API key and secret exposure in source code repositories, securing gen AI usage with policy controls, and reducing compliance risk in regulated industries like healthcare, finance, and education.

How to Use Nightfall AI

1. Connect your environment by integrating key SaaS apps, gen AI tools, repositories, and data stores.
2. Select or create policies that define which data types (PII, PHI, PCI, secrets) to detect and how to respond.
3. Enable detectors (contextual, regex, exact match, OCR) and tune sensitivity for your data landscape.
4. Run initial scans to inventory sensitive data and surface high-risk exposures.
5. Configure automated remediation actions such as redaction, link revocation, user coaching, or ticket creation.
6. Deploy the AI firewall to sanitize prompts/responses and enforce guardrails across gen AI applications.
7. Integrate with SIEM/SOAR for centralized alerting, escalation, and incident response.
8. Monitor dashboards and reports, refine policies, and track posture improvements over time.

Nightfall AI Use Cases

Healthcare organizations use Nightfall AI to detect and protect PHI across collaboration tools for HIPAA compliance; fintech and banking teams prevent PCI and PII leakage in customer communications and code; software companies secure secrets in Git and CI/CD; legal and professional services control data sharing with clients; education and public sector teams reduce overexposure in cloud drives; and enterprises adopt the AI firewall to govern LLM usage and redact sensitive data in prompts and outputs.

Nightfall AI Pricing

Nightfall AI typically offers tiered, subscription-based pricing that varies by coverage scope, data volume, and integrations. Plans are commonly tailored for SaaS security, gen AI governance, and developer use cases. Organizations usually engage sales for a quote, with demos and pilot evaluations available to validate policies and detection quality before wider rollout.

Pros and Cons of Nightfall AI

FAQs about Nightfall AI

• What data types can Nightfall AI detect?

  It identifies PII (names, emails, addresses), PHI, PCI (payment data), secrets like API keys and tokens, and even source code and images via OCR.

• How does the AI firewall work?

  It inspects prompts and responses to LLMs, redacts or masks sensitive content, and enforces policies to prevent data leakage during gen AI usage.

• Does Nightfall AI integrate with my existing tools?

  Yes, it offers connectors for popular SaaS apps and integrates with SIEM/SOAR platforms for centralized alerts and workflows.

• Can I create custom detection rules?

  You can build custom policies and detectors, including regex, exact data match, and context-aware rules tailored to your environment.

• Is remediation automated?

  Policies can automate actions like redaction, link revocation, user coaching, and ticketing, while allowing manual review for sensitive cases.