How It Works
Aiceberg provides enterprise-grade AI security with real-time, automated validation of all AI application traffic — speech, text, or source code.
Aiceberg allows you to unlock the potential of AI—without any of the risks.
Safety
Guardrails ensure only use case relevant AI interactions are permitted. Prevent unsanctioned, unsuitable, or illegal content. Ensure privacy and automatically redact personal or sensitive information.
Security
Ensure your security posture is always up to date for the latest attack vectors. AIceberg can detect common AI cybersecurity attack vectors like prompt injection and jailbreaking or perform sophisticated security analysis for agentic workflows.
Compliance
Get the highest degree of compliance, transparency, and auditability. Our explainable, non-generative AI models provide maximum accuracy and are auditable beginning to end so there’s no guessing.
Observability
Enterprise observability across all AI interactions. Understand what are common prompts, objectives, and intentions to constantly improve your user’s experience and gain valuable business intelligence from communication mining of prompt/response pairings.
Real-Time Risk Monitoring
Aiceberg takes a layered approach to safety, security, and compliance through observed AI. Acquire more context about user intent, identify appropriate information to service requests, control content shared with both users and AI, monitor instructions for malicious intent that could compromise your reputation or expose liability, and ensure alignment between models’ intended purpose and user intent.
Risk Signals Library
Robust and growing library of AI threat detection tools to help you power safe, secure, and compliant use of generative models across your enterprise.
PII
Discerning special entities such as social security numbers, date of birth, addresses, emails, etc.
PHI
Discerning special entities such as medical history, treatment information, insurance details, etc.
PCI
Discerning special entities such as credit card numbers, exp date, CVV
Secrets
Passwords, API Keys, crypto keys, etc.
Toxicity
Identifying and mitigating harmful or inappropriate language
Illegality
Preventing content that may violate laws
Blocklists
Restrict specific words, phrases, or topics from being processed or generated by the AI
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Relevance
Ensures the content generated is pertinent to the context of the interaction
Intent
Understanding and aligning with the user's purpose
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Input Manipulation
Tactics like prompt injection, instruction override, or direct command injection are identified and neutralized
Output Manipulation
Stops the leaking of prompts that could reveal sensitive information or internal system data
Goal Alignment
Ensures AI’s actions remain aligned with intended objectives and user directives.
Code Vulnerability
Syntactic instructions and semantic based attacks such as prompt injection, jailbreaking, prompt leaking or role impersonation
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Data Loss Protect
We analyze the content against the defined data loss ground truth and alert or enforce policy
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
Secrets
Passwords, API Keys, crypto keys, etc.
PII
Discerning special entities such as social security numbers, date of birth, addresses, emails, etc.
PHI
Discerning special entities such as medical history, treatment information, insurance details, etc.
PCI
Discerning special entities such as credit card numbers, exp date, CVV
Blocklists
Restrict specific words, phrases, or topics from being processed or generated by the AI
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Relevance
Ensures the content generated is pertinent to the context of the interaction
Intent
Understanding and aligning with the user's purpose
Toxicity
Identifying and mitigating harmful or inappropriate language
Illegality
Preventing content that may violate laws
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Input Manipulation
Tactics like prompt injection, instruction override, or direct command injection are identified and neutralized
Output Manipulation
Stops the leaking of prompts that could reveal sensitive information or internal system data
Goal Alignment
Prevents goal hijacking, ensuring that the AI's actions remain aligned with its intended purpose and user directives
Code Vulnerability
Syntactic instructions and semantic based attacks such as prompt injection, jailbreaking, prompt leaking or role impersonation
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Data Loss Protect
We analyze the content against the defined data loss ground truth and alert or enforce policy
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
Intent
Understanding and aligning with the user's purpose
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Sentiment
Gauges the emotional tone of generated content
Entity
Identifies the subject matter of prompts to contextualize interactions
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
Illegality
Preventing content that may violate laws
Blocklists
Restrict specific words, phrases, or topics from being processed or generated by the AI
PII
Discerning special entities such as social security numbers, date of birth, addresses, emails, etc.
PHI
Discerning special entities such as medical history, treatment information, insurance details, etc.
PCI
Discerning special entities such as credit card numbers, exp date, CVV
Secrets
Passwords, API Keys, crypto keys, etc.
Toxicity
Identifying and mitigating harmful or inappropriate language
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Intent
Understanding and aligning with the user's purpose
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Input Manipulation
Tactics like prompt injection, instruction override, or direct command injection are identified and neutralized
Output Manipulation
Stops the leaking of prompts that could reveal sensitive information or internal system data
Goal Alignment
Prevents goal hijacking, ensuring that the AI's actions remain aligned with its intended purpose and user directives
Code Vulnerability
Syntactic instructions and semantic based attacks such as prompt injection, jailbreaking, prompt leaking or role impersonation
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Data Loss Protect
We analyze the content against the defined data loss ground truth and alert or enforce policy
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Intent
Understanding and aligning with the user's purpose
Sentiment
Gauges the emotional tone of generated content
Entity
Identifies the subject matter of prompts to contextualize interactions
Code Vulnerability
Syntactic instructions and semantic based attacks such as prompt injection, jailbreaking, prompt leaking or role impersonation
Data Loss Protect
We analyze the content against the defined data loss ground truth and alert or enforce policy
Blocklists
Restrict specific words, phrases, or topics from being processed or generated by the AI
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Input Manipulation
Tactics like prompt injection, instruction override, or direct command injection are identified and neutralized
Output Manipulation
Stops the leaking of prompts that could reveal sensitive information or internal system data
System Instruct Class
Ensures that the model's responses and actions are in direct correspondence with the instructions provided by users
Relevance
Ensures the content generated is pertinent to the context of the interaction
High-Level Objective
Clarifying the overarching goals the AI should achieve in each interaction
Intent
Understanding and aligning with the user's purpose
Sentiment
Gauges the emotional tone of generated content
Entity
Identifies the subject matter of prompts to contextualize interactions
Toxicity
Identifying and mitigating harmful or inappropriate language
Intent-to-Instruct
Ensuring that AI correctly interprets and follows the intended instruction of a prompt while minimizing the risk of misalignment, harmful outputs, or unintended consequences
Illegality
Preventing content that may violate laws
Goal Alignment
Prevents goal hijacking, ensuring that the AI's actions remain aligned with its intended purpose and user directives
Text-to-SQL
Ensures accuracy and relevance in tasks that require precise language-to-code translation
Instruct-to-Action
Harmonizes the user's stated objectives and intents with the actual actions performed by the AI
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Relevance
Ensures the content generated is pertinent to the context of the interaction
PII
Discerning special entities such as social security numbers, date of birth, addresses, emails, etc.
PHI
Discerning special entities such as medical history, treatment information, insurance details, etc.
PCI
Discerning special entities such as credit card numbers, exp date, CVV
Secrets
Identifies and redacts sensitive system credentials such as API keys, passwords, and cryptographic keys.
Toxicity
Flags and mitigates harmful, inappropriate, or offensive content.
Illegality
Prevents the generation or dissemination of content that could violate laws.
Blocklists
Restricts AI responses involving predefined banned words, phrases, or topics.
High-Level Objective
Manages the presence of code in communications
Sentiment
Gauges the emotional tone of generated content
Entity
Identifies the subject matter of prompts to contextualize interactions
Goal Alignment
Prevents goal hijacking, ensuring that the AI's actions remain aligned with its intended purpose and user directives
Toxicity
Flags and mitigates harmful, inappropriate, or offensive content.
Illegality
Prevents the generation or dissemination of content that could violate laws.
Blocklists
Restricts AI responses involving predefined banned words, phrases, or topics.
Code Present
Manages the presence of code in communications
Code Requested
Ensures that executable content is only included when explicitly requested by the user
Input Manipulation
Tactics like prompt injection, instruction override, or direct command injection are identified and neutralized
Output Manipulation
Stops the leaking of prompts that could reveal sensitive information or internal system data
Code Vulnerability
Syntactic instructions and semantic based attacks such as prompt injection, jailbreaking, prompt leaking or role impersonation
Data Loss Protect
We analyze the content against the defined data loss ground truth and alert or enforce policy
Why Choose Aiceberg?
Dedicated to empowering enterprises on their AI journey, from day zero to scale, unlocking transformative value at every stage.
Purpose-Built
Never use a black box to police a black box. AI needs a human-centric control plane that is transparent, explainable, and comprehensive. AIceberg orchestrates 20+ non-generative, specialized models for comprehensive safety, security, and compliance coverage.
Future-Proof
Aiceberg works independently of AI applications, using the content of input and output to detect and eliminate risks. Our AI-agnostic approach uniquely positions us to accompany you through rapid technology changes, during which our platform performs as a long-term anchor and ground truth.
Grounded in Research
Aiceberg invested early in academic partnerships and our research lab so that leading data science principles guided our product development. Aiceberg was purpose-built to support your enterprise with metrics and insights on your safe, secure, and compliant adoption of AI.
Use Cases
Observe all AI and agentic interactions for any use case to power AI threat detection for secure, safe, and compliant adoption.
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