Overview
Product details compiled from public sources, each with a citation.
- Description
- AI observability and evaluation platform with run-time guardrails that screen LLM inputs and outputs, blocking jailbreaks, prompt injection, and PII while flagging hallucinated or unsafe responses.2
- Deployment
- SaaS, Self-hosted3agent
- Status
- Acquired5agent
- Acquisition
- Acquired by Dynatrace, announced 2026-08-13. It now operates as a standalone product.5agent
- Compliance
- SOC 2 Type 2, ISO 27001, HIPAA, PCI DSS, GDPR4agent (company-level, see Methodology)
Matrix Coverage
Where this product defends, by asset class and NIST CSF function. The Coverage column shows whether each asset is Primary, Secondary, or Adjacent to what the product does. The table omits empty rows and columns.
| Asset class | Protect | Detect | Coverage | Source |
|---|---|---|---|---|
| AI Coding and Orchestration Tools | Protect: Not covered | Secondary | 2 | |
| Runtime AI Data | Primary | 1 |
Framework Relevance
These frameworks include controls relevant to the asset classes Arize defends. This is an editorial inference from the AI Defense Matrix asset-level crossmap, not a statement that Arize AI implements these controls or is certified against them.
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| Framework | Asset class | Relevant controls |
|---|---|---|
| NIST IR 8596 | AI Coding and Orchestration Tools | Agents as deployed artifacts (orchestration view; see AI Agent Identities row for the principal view); system prompts and templates |
| Runtime AI Data | Prompts (runtime); inference data | |
| CSA AI Controls Matrix | AI Coding and Orchestration Tools | Application and Interface Security; Supply Chain Management |
| Runtime AI Data | Data Security and Privacy Lifecycle Management; Application and Interface Security | |
| ISO 42001 | AI Coding and Orchestration Tools | A.6 AI system life cycle; A.5 Assessing impacts of AI systems |
| Runtime AI Data | A.7 Data for AI systems; A.8 Information for interested parties | |
| Google SAIF | AI Coding and Orchestration Tools | Secure the AI supply chain; application and pipeline security; agent orchestration controls |
| Runtime AI Data | Expand AI red-teaming; runtime input and output safety; prompt defense | |
| SANS Critical AI Security Guidelines | AI Coding and Orchestration Tools | Secure Agentic Systems and AI Autonomy Controls (defined function scope; execution isolation; API and function-call gating); Limit Model Behavior (focused functionality; access controls outside the model) |
| Runtime AI Data | Model I/O Handling (sanitize, validate, and filter inputs and outputs; segregate user and system prompts; multilayered prompt-injection defense); Conventional Security Controls (protect augmentation and RAG data with vector-store access controls and validation); Data Minimization and Obfuscation (limit sensitive prompt content; context-window management); Limit Model Behavior (AI guardrails) | |
| MITRE ATLAS | AI Coding and Orchestration Tools | AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0016 Obtain Capabilities (malicious plugins) |
| Runtime AI Data | AML.T0051 LLM Prompt Injection; AML.T0054 LLM Jailbreak; AML.T0056 Extract LLM System Prompt (system prompt leaks as inference data; the AI Coding and Orchestration Tools row owns it as configuration) | |
| OWASP AI Exchange | AI Coding and Orchestration Tools | Development-time threats: agent framework supply chain; runtime threats: plugin abuse, prompt injection via tools |
| Runtime AI Data | Input threats: prompt injection, adversarial inputs, evasion; runtime threats: RAG poisoning, memory tampering | |
| OWASP LLM Top 10 | AI Coding and Orchestration Tools | LLM01 Prompt Injection; LLM05 Improper Output Handling; LLM07 System Prompt Leakage; LLM10 Unbounded Consumption |
| Runtime AI Data | LLM01 Prompt Injection; LLM02 Sensitive Information Disclosure; LLM08 Vector and Embedding Weaknesses; LLM05 Improper Output Handling | |
| OWASP Agentic Security Top 10 | AI Coding and Orchestration Tools | ASI01 Agent Goal Hijack; ASI02 Tool Misuse and Exploitation; ASI05 Unexpected Code Execution (RCE); ASI07 Insecure Inter-Agent Communication; ASI08 Cascading Failures; ASI10 Rogue Agents |
| Runtime AI Data | ASI06 Memory & Context Poisoning; ASI01 Agent Goal Hijack (via prompt injection in runtime inputs) |
Provenance
Last sourced 2026-06-09.
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Sources
- Arize AX guardrails
- “Failed messages trigger corrective actions such as default responses, retries, or blocking outputs entirely.”
- Arize production LLM evaluation
- “LLM guardrails work in real-time to either catch dangerous user inputs or screen model outputs.”
- Arize AX self-hosted deployment
- “Deploy Arize AX in your own environment”
- Arize AI Trust Center
- “Arize AI Announces SOC 2 Type II Certification”
- Dynatrace completes acquisition of Arize
- “Arize will continue supporting both Phoenix, its open-source platform, and AX, its enterprise platform.”
Changelog
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Recorded the acquisition by Dynatrace, announced on 2026-08-13 and completed on 2026-10-01.
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Updated the deployment options and compliance attestations.
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Enriched from the Arize documentation.
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