nAlert AI provides an end-to-end generative AI security platform that enhances the security of AI applications and workflows across industries such as healthcare, finance, and retail. The platform addresses vulnerabilities, data privacy violations, and adversarial attacks by offering risk analysis, compliance management, and real-time threat detection to protect sensitive information and ensure the integrity of AI systems.
Funding
Funding not disclosed
Founders
Product
Problem
Generative AI applications are vulnerable to a range of security threats, including adversarial attacks, data privacy violations, and model theft, which can lead to significant breaches and enterprise fallouts. Existing security measures often fail to address the unique vulnerabilities present in AI applications and workflows.
Solution
nAlert AI provides an end-to-end security platform designed to enhance the security and integrity of generative AI applications and workflows. The platform offers comprehensive risk analysis, compliance management, and real-time threat detection to protect sensitive information and ensure the reliability of AI systems. nAlert AI helps organizations uncover security blind spots, detect adversarial threats, manage model vulnerabilities, and enhance privacy with domain-specific guardrails. The platform integrates with leading AI platforms and provides AI forensics, governance, and compliance tools to ensure a secure way to use AI for business.
Target Audience
The platform is designed for enterprises across industries such as healthcare, finance, and retail that are deploying generative AI applications and need to ensure their security and compliance.
Features
- AI asset discovery and inventory to track models, LLMs, training pipelines, and compute resources
- Automated LLM and model vulnerability scanning with domain-specific integrations and recommendations
- Adversarial threat detection using indicators of attack (IOA) and compromise (IOC)
- Data privacy alerts with detection, redaction, and obfuscation of PII and PHI
- AI lineage tracking to identify data sources, types, and versions to detect data contamination attacks
- Prompt security and integrity monitoring to prevent prompt injections and ensure secure LLM tokenization
- AI forensics with audit trails, feedback loops, and accountability reports
- Integration with SIEM for enriched AI Detection & Response (ADR) events
- 360-degree visibility across AI environments, including data, models, pipelines, and evaluations