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Trusys vs Arize
Arize is a leading AI observability and evaluation platform. Trusys is the governance layer above it — agentic policy enforcement, runtime guardrails, security red-teaming, and compliance automation, unified by Argus as the governance intelligence brain.
Book Demo
Get Started
Observability tells you what your AI did. Governance tells you what to do about it — at runtime, in front of a regulator, and on a board agenda.
At-a-Glance Comparison
See how Arize and Trusys compare across key capabilities
Capability
Primary category
Primary buyer
Tracing and span-level observability
LLM evaluation
Prompt optimization and experimentation
Adversarial red-teaming as a service
Native runtime guardrail enforcement
Agentic policy enforcement (tool-call control)
Runtime behavioral monitoring
AI system inventory and registry
Unified risk scoring across lifecycle
Regulatory mapping (EU AI Act, NIST AI RMF, ISO 42001)
Sector-specific compliance (SR 11-7, DORA, MAS FEAT, RBI, DPDP, GDPR)
Board-reportable assurance evidence
Audit evidence packs for examiners
Deployment
Arize
AI observability and evaluation
AI/ML engineering teams
✓ Best-in-class
✓
✓
-
Integrations only
-
✓ via traces
-
-
-
-
-
-
SaaS, self-hosted (Phoenix)
Trusys
AI governance and assurance
AI AI risk teams, security teams, compliance teams, product teams, enterprise AI ownersrisk teams, security teams, compliance teams, product teams, enterprise AI owners
Ingested via OTel and integrations
✓ TruEval
✓
✓
✓ TruGuard
✓ TruGuard for agents
✓ TruPulse
Audit-ready evidence, risk reports, policy violations, monitoring history
Audit-ready evidence, risk reports, policy violations, monitoring history
Audit-ready evidence, risk reports, policy violations, monitoring history
Audit-ready evidence, risk reports, policy violations, monitoring history
Audit-ready evidence, risk reports, policy violations, monitoring history
✓ Argus
SaaS, customer VPC, on-prem
The structural difference: observability vs governance
Arize and Trusys are often compared, but they solve different problems in the AI stack
Observability
Visibility. Spans, traces, evaluations, prompt-level debugging, latency, token cost, retrieval quality, drift. Observability tells an engineering team what is happening inside an AI application. Arize is one of the strongest products in this category.
Governance
Control. Policy enforcement at the inference boundary, security red-teaming before launch, agent action constraints at runtime, regulatory mapping, audit evidence, board-reportable assurance, incident workflows. Governance tells a CISO, CRO, or regulator whether what is happening is acceptable — and stops the unacceptable from reaching the user.
You need both. They are not the same layer, and one cannot substitute for the other.
Best Fit
Where Trusys goes further
Runtime policy enforcement, not just observation
Arize observes. It does not natively enforce policy at the inference boundary. To enforce, you have to bolt on a separate guardrails library — Guardrails AI, NeMo Guardrails, Lakera, LLM Guard — and integrate it yourself.
TruGuard is a first-class runtime enforcement product. PII redaction, prompt injection blocking, jailbreak detection, advice-boundary enforcement for regulated industries, topical restriction, output validation, agent tool-call policy, and 40+ other validators — all running inline at the inference boundary, configurable per use case, with policy decisions written to Argus as governance evidence.
The distinction matters because observability sees the leakage after it has happened. Enforcement prevents it.
Security red-teaming as a product, not an integration
Arize evaluates against custom metrics. It does not run structured adversarial red-team campaigns against your AI systems.
TruEval includes a comprehensive adversarial test library mapped to OWASP LLM Top 10 and OWASP Top 10 for Agentic AI — prompt injection, jailbreaks, indirect injection via retrieved content, supply-chain attacks, agent takeover, sensitive-information disclosure, output handling abuse, excessive agency, model denial-of-service, model theft, and more. Tests run pre-deployment and re-run on every model update, with results feeding Argus as ongoing security evidence.
Trusys also runs structured red-team engagements as a service — independent adversarial assurance for organisations that need third-party evidence in front of regulators and auditors.
Agentic AI: from tracing agents to governing them
Arize traces agents — span-level visibility into reasoning steps, tool calls, and agent decisions. Trusys governs them.
What that means concretely:
TruGuard for agents enforces tool-call policy at runtime — which tools an agent may invoke, with which arguments, under which conditions, with which approval workflow for high-risk actions.
TruPulse for agents monitors behavioural deviation — when an agent starts taking unusual action sequences, escalating privileges, or pattern-matching to known abuse signatures.
Argus for agents maintains the agent registry — every agent, its risk classification, its allowed action set, its incident history, its OWASP Agentic Top 10 posture, and its evidence trail.
Tracing an agent that just exfiltrated data is observability. Stopping the exfiltration before it lands and producing the regulator-facing incident report afterwards is governance.
Compliance automation, not just dashboards
Arize provides engineering dashboards. It does not natively map signals to EU AI Act articles, NIST AI RMF subcategories, ISO 42001 controls, OWASP LLM Top 10 categories, SR 11-7 expectations, DPDP obligations, or any of the regulatory regimes that determine whether your AI program is auditable.
Argus does this natively. Every evaluation result, every guardrail block, every runtime anomaly, every incident is mapped — at ingestion time — to the relevant control under every framework your organisation reports against. Evidence packs are generated on demand, in the format a regulator, an internal auditor, or a board audit committee actually wants.
This is the difference between we have data and we can prove we are governed.
Argus — the layer Arize does not have
This is the heart of the Trusys value proposition for any organisation that has outgrown pure observability.
Argus is the AI governance intelligence layer. It is the system of record for every AI system in your organisation — every model, every agent, every prompt, every RAG pipeline, every dataset, every evaluation, every guardrail event, every runtime incident.
Argus does what no observability platform does:
1
Maintains the AI inventory
A live registry of every AI system, its purpose, its data exposure, its owner, its models, its risk classification.
2
Correlates signals across the lifecycle
Evaluation results from TruEval, runtime decisions from TruGuard, behavioural signals from TruPulse — and from external sources including Arize traces — are correlated into a unified risk score per system.
3
Maps every signal to regulation
EU AI Act, NIST AI RMF 1.0, ISO/IEC 42001, OWASP LLM Top 10, OWASP Agentic Top 10, SR 11-7, DORA, PRA SS1/23, MAS FEAT, HKMA AI guidance, CBUAE, RBI FREE-AI, DPDP, GDPR, SOC 2.
4
Produces audit-ready evidence
Evidence packs, board reports, incident narratives, and supervisor-facing documentation, generated on demand in the format the audience requires.
For an organisation whose AI footprint has grown beyond what an engineering team alone can govern, this is the missing layer.
Framework
Why OWASP Top 10Matters to Your Business?
We have a lot of respect for Arize. It is one of the most mature platforms in the AI observability category, and we recommend it for the cases it was built for:
Span-level tracing
Built on OpenTelemetry, with deep instrumentation across OpenAI Agents SDK, Claude Agent SDK, LangGraph, CrewAI, AutoGen, Google ADK, Pydantic AI, LlamaIndex, DSPy, Vercel AI SDK, and many more.
Trace-native evaluation
Strong evaluation workflows tied directly to production traces, with custom evaluator support and LLM-as-judge.
Prompt experimentation and optimization
Strong dev-loop ergonomics for prompt engineers iterating on quality.
Drift and quality monitoring
Mature monitoring derived from Arize's heritage in ML observability.
Open-source presence
Phoenix is a popular, well-maintained open-source platform with active community.
Engineering UX
Built for ML and AI engineers debugging at the trace level.
If you are an AI engineering team that needs to see, debug, and optimize what your models and agents are doing, Arize is one of the best tools you can pick. The rest of this page is about what happens when observing is no longer enough — when the question becomes what are we going to enforce, what will we tell the regulator, and what does the board see.
Frequently Asked Questions
01.
Is Trusys an Arize alternative?
For governance, yes. For pure observability and tracing, Arize remains a strong choice — many of our customers run both, with Arize for the engineering layer and Trusys for the governance layer.
02.
Can Trusys govern agentic AI?
Yes. TruGuard enforces agent tool-call policy at runtime, TruPulse monitors agent behavioural deviation, and Argus maintains the agent registry mapped to OWASP Top 10 for Agentic AI. Trusys is designed specifically for the governance of agentic systems, not only LLM applications.
03.
Does Trusys work with all model providers?
Yes. Trusys is fully model-agnostic — OpenAI, Anthropic, Google, Meta, Mistral, AWS Bedrock, Azure OpenAI, and customer-fine-tuned and open-weight models in private infrastructure.
04.
How does Argus compare to Arize's Alyx?
Alyx is Arize's AI assistant for debugging traces and identifying failure patterns in the engineering workflow. Argus is the governance intelligence layer — the AI system of record, the regulatory mapping engine, and the evidence-generation layer for the governance function. They serve different audiences and solve different problems.
05.
Does Trusys do tracing like Arize?
Trusys ingests traces via OpenTelemetry and integrates with observability platforms including Arize. Our focus is on what happens with that data — policy enforcement, security testing, behavioural monitoring, and compliance automation — rather than on being the best trace UI for engineers.
Trusys Advantage
Govern what your observability platform reveals
Trusys is the governance layer for AI — policy enforcement, security red-teaming, behavioural monitoring, and compliance automation, unified by Argus. It works alongside Arize and other observability platforms, and it is what your CISO, CRO, and audit committee actually need.
Book a Demo
Trusys vs Arize
Arize is a leading AI observability and evaluation platform. Trusys is the governance layer above it — agentic policy enforcement, runtime guardrails, security red-teaming, and compliance automation, unified by Argus as the governance intelligence brain.
Book Demo
Get Started
Observability tells you what your AI did. Governance tells you what to do about it — at runtime, in front of a regulator, and on a board agenda.
At-a-Glance Comparison
See how Arize and Trusys compare across key capabilities
Capability
Primary category
Primary buyer
Tracing and span-level observability
LLM evaluation
Prompt optimization and experimentation
Adversarial red-teaming as a service
Native runtime guardrail enforcement
Agentic policy enforcement (tool-call control)
Runtime behavioral monitoring
AI system inventory and registry
Unified risk scoring across lifecycle
Regulatory mapping (EU AI Act, NIST AI RMF, ISO 42001)
Sector-specific compliance (SR 11-7, DORA, MAS FEAT, RBI, DPDP, GDPR)
Board-reportable assurance evidence
Audit evidence packs for examiners
Deployment
Arize
AI observability and evaluation
AI/ML engineering teams
✓ Best-in-class
✓
✓
-
Integrations only
-
✓ via traces
-
-
-
-
-
-
SaaS, self-hosted (Phoenix)
Trusys
AI governance and assurance
CISO, Chief AI Officer, Head of GRC, Head of Model Risk
Ingested via OTel and integrations
✓ TruEval
✓
✓
✓ TruGuard
✓ TruGuard for agents
✓ TruPulse
✓ Argus
✓ Argus
✓ Argus
✓ Argus
✓ Argus
✓ Argus
SaaS, customer VPC, on-prem
The structural difference: observability vs governance
Arize and Trusys are often compared, but they solve different problems in the AI stack
Observability
Visibility. Spans, traces, evaluations, prompt-level debugging, latency, token cost, retrieval quality, drift. Observability tells an engineering team what is happening inside an AI application. Arize is one of the strongest products in this category.
Governance
Control. Policy enforcement at the inference boundary, security red-teaming before launch, agent action constraints at runtime, regulatory mapping, audit evidence, board-reportable assurance, incident workflows. Governance tells a CISO, CRO, or regulator whether what is happening is acceptable — and stops the unacceptable from reaching the user.
You need both. They are not the same layer, and one cannot substitute for the other.
Best Fit
Where Trusys goes further
Runtime policy enforcement, not just observation
Arize observes. It does not natively enforce policy at the inference boundary. To enforce, you have to bolt on a separate guardrails library — Guardrails AI, NeMo Guardrails, Lakera, LLM Guard — and integrate it yourself.
TruGuard is a first-class runtime enforcement product. PII redaction, prompt injection blocking, jailbreak detection, advice-boundary enforcement for regulated industries, topical restriction, output validation, agent tool-call policy, and 40+ other validators — all running inline at the inference boundary, configurable per use case, with policy decisions written to Argus as governance evidence.
The distinction matters because observability sees the leakage after it has happened. Enforcement prevents it.
Security red-teaming as a product, not an integration
Arize evaluates against custom metrics. It does not run structured adversarial red-team campaigns against your AI systems.
TruEval includes a comprehensive adversarial test library mapped to OWASP LLM Top 10 and OWASP Top 10 for Agentic AI — prompt injection, jailbreaks, indirect injection via retrieved content, supply-chain attacks, agent takeover, sensitive-information disclosure, output handling abuse, excessive agency, model denial-of-service, model theft, and more. Tests run pre-deployment and re-run on every model update, with results feeding Argus as ongoing security evidence.
Trusys also runs structured red-team engagements as a service — independent adversarial assurance for organisations that need third-party evidence in front of regulators and auditors.
Agentic AI: from tracing agents to governing them
Arize traces agents — span-level visibility into reasoning steps, tool calls, and agent decisions. Trusys governs them.
What that means concretely:
TruGuard for agents enforces tool-call policy at runtime — which tools an agent may invoke, with which arguments, under which conditions, with which approval workflow for high-risk actions.
TruPulse for agents monitors behavioural deviation — when an agent starts taking unusual action sequences, escalating privileges, or pattern-matching to known abuse signatures.
Argus for agents maintains the agent registry — every agent, its risk classification, its allowed action set, its incident history, its OWASP Agentic Top 10 posture, and its evidence trail.
Tracing an agent that just exfiltrated data is observability. Stopping the exfiltration before it lands and producing the regulator-facing incident report afterwards is governance.
Compliance automation, not just dashboards
Arize provides engineering dashboards. It does not natively map signals to EU AI Act articles, NIST AI RMF subcategories, ISO 42001 controls, OWASP LLM Top 10 categories, SR 11-7 expectations, DPDP obligations, or any of the regulatory regimes that determine whether your AI program is auditable.
Argus does this natively. Every evaluation result, every guardrail block, every runtime anomaly, every incident is mapped — at ingestion time — to the relevant control under every framework your organisation reports against. Evidence packs are generated on demand, in the format a regulator, an internal auditor, or a board audit committee actually wants.
This is the difference between we have data and we can prove we are governed.
Argus — the layer Arize does not have
This is the heart of the Trusys value proposition for any organisation that has outgrown pure observability.
Argus is the AI governance intelligence layer. It is the system of record for every AI system in your organisation — every model, every agent, every prompt, every RAG pipeline, every dataset, every evaluation, every guardrail event, every runtime incident.
Argus does what no observability platform does:
1
Maintains the AI inventory
A live registry of every AI system, its purpose, its data exposure, its owner, its models, its risk classification.
2
Correlates signals across the lifecycle
Evaluation results from TruEval, runtime decisions from TruGuard, behavioural signals from TruPulse — and from external sources including Arize traces — are correlated into a unified risk score per system.
3
Maps every signal to regulation
EU AI Act, NIST AI RMF 1.0, ISO/IEC 42001, OWASP LLM Top 10, OWASP Agentic Top 10, SR 11-7, DORA, PRA SS1/23, MAS FEAT, HKMA AI guidance, CBUAE, RBI FREE-AI, DPDP, GDPR, SOC 2.
4
Produces audit-ready evidence
Evidence packs, board reports, incident narratives, and supervisor-facing documentation, generated on demand in the format the audience requires.
For an organisation whose AI footprint has grown beyond what an engineering team alone can govern, this is the missing layer.
Framework
Where Arize is genuinely strong
We have a lot of respect for Arize. It is one of the most mature platforms in the AI observability category, and we recommend it for the cases it was built for:
Span-level tracing
Built on OpenTelemetry, with deep instrumentation across OpenAI Agents SDK, Claude Agent SDK, LangGraph, CrewAI, AutoGen, Google ADK, Pydantic AI, LlamaIndex, DSPy, Vercel AI SDK, and many more.
Trace-native evaluation
Strong evaluation workflows tied directly to production traces, with custom evaluator support and LLM-as-judge.
Prompt experimentation and optimization
Strong dev-loop ergonomics for prompt engineers iterating on quality.
Drift and quality monitoring
Mature monitoring derived from Arize's heritage in ML observability.
Open-source presence
Phoenix is a popular, well-maintained open-source platform with active community.
Engineering UX
Built for ML and AI engineers debugging at the trace level.
If you are an AI engineering team that needs to see, debug, and optimize what your models and agents are doing, Arize is one of the best tools you can pick. The rest of this page is about what happens when observing is no longer enough — when the question becomes what are we going to enforce, what will we tell the regulator, and what does the board see.
Frequently Asked Questions
01.
Is Trusys an Arize alternative?
For governance, yes. For pure observability and tracing, Arize remains a strong choice — many of our customers run both, with Arize for the engineering layer and Trusys for the governance layer.
02.
Can Trusys govern agentic AI?
Yes. TruGuard enforces agent tool-call policy at runtime, TruPulse monitors agent behavioural deviation, and Argus maintains the agent registry mapped to OWASP Top 10 for Agentic AI. Trusys is designed specifically for the governance of agentic systems, not only LLM applications.
03.
Does Trusys work with all model providers?
Yes. Trusys is fully model-agnostic — OpenAI, Anthropic, Google, Meta, Mistral, AWS Bedrock, Azure OpenAI, and customer-fine-tuned and open-weight models in private infrastructure.
04.
How does Argus compare to Arize's Alyx?
Alyx is Arize's AI assistant for debugging traces and identifying failure patterns in the engineering workflow. Argus is the governance intelligence layer — the AI system of record, the regulatory mapping engine, and the evidence-generation layer for the governance function. They serve different audiences and solve different problems.
05.
Does Trusys do tracing like Arize?
Trusys ingests traces via OpenTelemetry and integrates with observability platforms including Arize. Our focus is on what happens with that data — policy enforcement, security testing, behavioural monitoring, and compliance automation — rather than on being the best trace UI for engineers.
Trusys Advantage
Govern what your observability platform reveals
Trusys is the governance layer for AI — policy enforcement, security red-teaming, behavioural monitoring, and compliance automation, unified by Argus. It works alongside Arize and other observability platforms, and it is what your CISO, CRO, and audit committee actually need.
Book a Demo