• AI Security Reconnaissance
• AI Compliance Provenance
• AI Traceability
• Tool/MCP/Supply Chain Audit
• Actionable Governance
• AI Policy Enforcement & Readiness CCPA , GDPR, NIST AI RMF, ISO/IEC 42001,EU/AI Act & DORA (Art. 52/53 Compliance), Healthcare AI HIPAA, Finance AI FINTRAC.

Multi-provider,  Multi-Agent, Multi-modal AI security, governance, cost, performance controls satisfying the strict AI risk-mitigation requirements.

Our Key Differentiator

• The Gap: 2025 “Reasoning Models” (like OpenAI o1/o3 or DeepSeek R1) generate thousands of “Chain of Thought” tokens that are billed but often hidden from the final API response.
• Our Differentiator: By explicitly knowing  reasoning tokens and effort analytics  our implementation captures 100% of the billable footprint. This prevents the “40-60% invisible bill” common in legacy dashboards and enables true FINRA-grade financial auditing.

• The Gap: Security leaks often happen via document uploads (PII in a PDF) or image metadata that bypasses standard text filters.
• Our Differentiator: The architecture includes a AlertAI Document Scanner and  tracking. It resolves retrieval URLs for attachments, allowing the AlertAI security watchdog to scan the content of a file (OCR/Text Extraction) before it reaches the model, closing the multi-modal exfiltration loophole.

• The Gap: In 2025, LLMs use tools. Without tracking specific session correlation in-context aggregation values, you cannot prove which tool was triggered by which model thought.
• Our Differentiator: We implement Stateful Agentic Auditing the gateway creates a deterministic audit trail. If an agent performs an unauthorized database delete, you have the “smoking gun” linking the model’s reasoning to the specific system action.

• The Gap: SSE (Streaming) connections can stay open for minutes. Inefficient memory management leads to “Memory Death Spirals.”
• Our Differentiator: This gateway uses a Non-Destructive Reactive Interceptor. Using the AlertAI “Zero-Leak” Pattern, we inspect streaming in real-time without latency, in memory. This allows for 10x higher concurrency compared to legacy “buffer-and-scan” proxies.

• The Gap: 2025 regulations (EU AI Act Art. 52/53) require real-time transparency—users must know content is AI-generated at the moment of consumption.
• Our Differentiator: The signals in-flight mid-stream allows the AlertAI AI security gateway to automatically inject mandatory transparency notices or block content that violates regional data residency (GDPR/DORA) before the first byte is even displayed to the user.

• The Gap: The industry is moving toward MCP, a universal standard for how agents connect to data.
• Our Differentiator: By natively detecting this gateway is future-proofed for the 2025 ecosystem. It can govern interactions not just between a user and a model, but between a model and its surrounding ecosystem of tools and local data sources.

Why is this the 2025 Gold Standard?

AlertAI  AI security governance policy gateway is not a passive observer but  an active gatekeeper, which is the defining requirement for enterprise AI in 2025.

Key Changes for 2025 Agentic AI  Auditing:

Unique Traceability

Our SecurityWatchdog able to policy control  Every AI Interaction in Real-Time whether the Agentic, the LLM, or the RAG, or AI Tool.

Provider Interoperability

Every AI Provider is supported in our 2025 state-of-art platform through 100+ AI Integrations.

Stateful Correlation

For 2025 “Agentic” workflows, fully ready for batch, streaming, multi-modal , including Azure OpenAI, Aws Bedrock, Google Vertex AI, Anthropic 2025 Claude 4.x models.

Based on current 2025 AI governance standards, the SecurityWatchdog can trigger the following policy actions:

1. Immediate Intervention (Hard Actions)

BLOCK: Terminates the request or response immediately if a critical violation (e.g., severe PII leak or high-risk prompt injection) is detected.
REDACT / MASK: Dynamically replaces sensitive information, such as credit card numbers, API keys, or personal identifiers, with placeholders (e.g., [REDACTED]) before the data reaches the provider or the user.
FAILOVER / REROUTE: If a specific model or provider becomes non-compliant or fails a security check, the watchdog can automatically route the query to a pre-approved, “safe” alternative model.

2. Adaptive Governance (Soft Actions)

THROTTLE: Applies behavioral rate limiting. Unlike standard API throttling, this is based on semantic intent—if a user is repeatedly probing for system prompts or sensitive data, their allowed request frequency is reduced.
HUMAN-IN-THE-LOOP (HITL): Pauses high-impact actions (e.g., financial transfers or database deletions initiated by an agent) and flags them for manual approval by a human administrator.
INJECT GUARDRAILS: Dynamically modifies the system prompt to include additional constraints (e.g., “Do not reveal internal file paths”) if the user’s request is deemed “borderline” or high-risk.

3. Observability & Forensic Actions

ALERT: Generates real-time notifications to security teams via integrated platforms (e.g., Slack, PagerDuty) when unusual patterns or policy near-misses occur.
LOG & AUDIT: Records the full context of a violation—including the call_id, trace_id, and reasoningTokens—to a centralized, immutable audit log (e.g., Kafka) for SOC2/DORA compliance.
QUARANTINE: Isolates suspicious payloads or file attachments for deep inspection (Malware/DLP scanning) before they are fully processed.

4. Financial & Operational Control

QUOTA ENFORCEMENT: Blocks or warns users when they approach their allocated token or cost budget for a specific period to prevent “Denial of Wallet” attacks.
MODERATION REROUTING: Automatically sends risky content through a secondary moderation pipeline (e.g., Azure AI Content Safety) for a deeper “vibe check” before releasing it to the end user.

Comprehensive AI  Security: Unlike many products that focus on a single aspect, Alert AI provides security controls across the entire AI development lifecycle, from data acquisition and model development to deployment, and  protects Enterprise AI Tools, Enterprise AI Applications, AI workloads, AI Agents alike.

• AI Security Gateway
• AI Policy Gateway
• Inline/Offline, no code changes require
• AI Access, Data leakage,Content Security, Resiliency, Cost, Resource control via gateway
• Holistic Platform for AI Agents Security, GenAI Apps and AI Tools & Supply Chain
• Integrates throughout existing development and SecOps workflows
• Automated AI red teaming
• AIBOM generation
• Full AI lifecycle security (development to runtime)
• Autonomous operations
• Autonomous Policy Control
• Self-Healing, Cost &  AI resiliency

Alert AI “Secure AI Anywhere” – AI Security gateway as Cloud Native Services offer:

1. AI Agents, LLM Applications Security
2. Autonomous AI Policy Control
3. AI Guardrails, RAG Policy control
4. AI Access Security
5. AI Prompt Security
6. Automatic LLM Vulnerability Scans
7. Self-healing, Cost, AI Resilience
8. AI Content Policies
9. AI Tool, MCP, CoPilot Security
10. AI Supply Chain Security (AI BOM)
11. AI Governance
12. AI Forensics

How Alert AI Security Gateway  Works?

• Inline & Offline AI Security Gateway:  AI security gateway with its multi-layers defense in depth, AI Access security, AI Runtime security, AI Policeis, guardrails, Prompt, Content Security, Moderation, Blocking and Allowing  all AI Interactions of GenAI , Agentic AI applications.

• Agentic AI security:  AI agents can interact with multiple systems, Alert AI offers security controls and  protections for the “Internet of Agents.” This includes protecting against Agent hallucinations, Data leakage, and Integrity attacks, Context Attacks, Tool poisoning, Shadow/Rogue AI Agents in complex, multi-agent workflows.

• Adversarial AI threat detection: Data Poisoning, Evasion, and Inference-time attackss using indicators of attack (IoA) and indicators of copromise (IoC) and  threat DB to identify manipulated inputs and compromised integrity.

• AI Security Lake (AISL):   AI Security signals, AI Security Data points for Detection Learning scalable up to order of millions to trillions if needed, AI Interactions, Metrics, Events, Logs, Traces from AI Agents, AI Applications, AI Infrastructure.
• AI Security Analytics:  Real-Time, Offline  Security Analytics, Security feature extraction, Aggregations, Threat and Incident detection end to end full AI life-cycle.
• AI Incidents & Response (AIDR) : Alerting in real-time, Autonomous Incident Resolution, Auto configuring, Autonomous AI Policy Control and Self-healing AI Agents.

• Domain-specific security guardrails: AI Policies can be customized with domain-specific guardrails, such as filtering sensitive information like PII (Personally Identifiable Information) and PHI (Protected Health Information).

• AI Asset tracking:  AI Agent Models, GenAI Applicaitons, Agentic AI Tools,Experiments, Evaluations, Datasets, Runs, Jobs, Versions catalog, listing, tracking, reports.

• Continuous Posture assessment: Moving beyond static security snapshots, the platform continuously monitors the security posture of AI assets, identifying misconfigurations and vulnerabilities in real-time. It then prioritizes risks by correlating data sensitivity with factors like permissions and vulnerabilities.

• Enhanced AI Forensics and AI Governance: Alert AI aggregates AI incidents to provide detailed “incident footprint reports” that allow for rapid root cause analysis. This supports robust auditing for compliance with regulations like GDPR and HIPAA.

Alert AI “Secure AI anywhere” AI Security Gateway

• “Secure AI Anywhere” Zero Trust: The gateway is a “Zero Trust AI” solution that provides robust security regardless of where the AI models are running—locally, on-premise, or in the cloud. It enforces granular access policies based on identity, device, and location.
• Zero-code deployment: The gateway can be deployed quickly and manages AI applications without requiring any changes to the underlying application code. This simplifies integration and accelerates the time-to-market for AI-powered features as applications built and run on any platform, any LLM, any data.
• RAG Shield protection: For Retrieval Augmented Generation (RAG) systems, the gateway includes a specialized RAG Shield. This protects against data manipulation and misinformation by ensuring the integrity of the retrieved data used to augment the AI model’s responses 
• AI Agent, MCP, Tool protection:  Automated run-time controls for Agentic AI Applications, AI Tool Access, Context Security,  Tool invocations, Data leakage.
• Multi-layered Prompt security: In addition to standard content security, moderation policies, the gateway uses a proprietary Domain Specific Language (DSL) to craft advanced prompt security rules. This enables more sophisticated threat detection for prompt-injection attacks, data leakage.
• AI Red teaming service, Integrated Vulnerability scanning: The gateway offers powerful, automatic, continuous vulnerability scanning and AI Red teaming service for LLMs, RAG Applications and AI agents. Offline, Inline test modes, Synthetic data generation, Provides integrations and support for easy and automated configurations for multiple providers, scanners, classifiers including NVIDIA Garak, PyRIT, and LLMFuzzer.
• AI Integrity Monitoring: Detect Data degradation, Data quality issues, model collapse, data governance, mitigate bias. Secure data pipelines, track lineage, Detect data poisoning where attackers inject malicious or corrupt data, Automated detection, Track and Alert Factual, Ground truth, Relevancy, Accuracy scores
  Score, forecast explainability and transparency trends. 
• AI  supply chain security: It assesses the security risks of third-party LLMs versions, AI models, classfiers and datasets, giving organizations audit and control over the components they integrate into their systems.

Discover, track, alert on insecure AI access,  unusual patterns of AI Agents. Trace back to single point-of-origin  with AI lineage. 360 view  command, control,  reconnaissance,  lateral movements.

Detect Adversarial threats on LLMs, Poison, Evasion, Exfiltration, Infiltration, feature corruption attacks using IOC, IOA’s, threat intelligence. Detect malicious injected exploitable deltas.

Automated LLM and AI Agent Vulnerability scans. Domain-specific integration.  AI Agent, LLM, Prompt, RAG Vulnerability DB.

Training, Evaluation, Inference analytics, Log anomaly detection, Metric anomaly detection, Model behavior analytics,  Prompt usage analytics, detect corrupt outputs. Severity, Explainability, Compliance scores. Recommendations, Reviews.

Use domain-specific guardrails. Audit upstream dependency pipelines.
Integrity verifications at runtime. Detect tokenizer manipulations in LLMs. Pro-active Tracking to stop AI supply chain attacks.

Ensure security controls to LLM’s ready for enterprise infrastructure.
Assign the AI service roles on the AI resource’s to Managed identities.
SPOT and STOP Attacks your AI compute, gpu, ext,int traffic, denial  attacks.

Detect, Redact, Alert Sensitive information disclosures, Data privacy violations, PII, PHI, Copyright Legal exposures in all Generative AI applications in environment.

Interoperable with your GenAI stack integrations with top providers, platforms, tools.

Enriched ADR (AI Detection  & Response) events with Alert data and forward to SIEM.