AIAI Governance StackFree kit

Arize AI vs Superwise

Both compete in Observability & Monitoring. Arize AI positions itself as “AI observability and evaluation platform for ML models, LLM apps, and agents”, while Superwiseleads with “Agentic Management Platform for building, monitoring, and governing AI at scale”. The table below compares what each publishes.

Where Arize AI pulls ahead

Publishes support for SOC 2, HIPAA, GDPR, which Superwise does not. AI engineering and ML teams wanting unified LLM/agent observability and evaluation with an open-source (Phoenix) on-ramp to enterprise-scale monitoring

Where Superwise pulls ahead

Regulated enterprises and AI platform teams needing a unified governance control plane spanning observability, guardrails, and policy enforcement for models and agents

PositioningAI observability and evaluation platform for ML models, LLM apps, and agentsAgentic Management Platform for building, monitoring, and governing AI at scale
CategoryObservability & MonitoringObservability & Monitoring
FrameworksSOC 2, HIPAA, GDPRNone published
DeploymentSaaS, Cloud, On-prem, Open-source, APISaaS, Cloud, On-prem, API
Built forData Science / ML, Risk, ComplianceData Science / ML, Risk, Compliance, GRC, Security
Founded20202019
HeadquartersBerkeley, California, USATel Aviv, Israel
OwnershipPrivate, independent, venture-backed (as of mid-2026)Acquired by Blattner Technologies in January 2023 (terms undisclosed); operates as a Blattner Tech company as of mid-2026
Funding~$135M total raised across 5 rounds, including a $70M Series C in February 2025 led by Adams Street Partners; earlier $38M Series B (2022) led by TCV~$4.6M in seed funding (including a $4.5M round in March 2020 led by Capri Ventures and F2 Capital) prior to the 2023 acquisition
PricingFree open-source (Phoenix); commercial tiers with free/self-serve entry and enterprise plans (usage/seat-based, custom pricing)Commercial enterprise SaaS; custom pricing
Key capabilities
  • End-to-end agent and LLM tracing
  • Evaluation framework (span/trace/session evals, LLM-as-judge)
  • Drift and performance monitoring
  • Embedding and data quality analysis
  • Bias/fairness monitoring
  • Prompt testing and iteration
  • Agentic Management Platform (governance control plane)
  • Agent Studio for governed agent deployment
  • Sub-10ms runtime guardrails (PII, jailbreak blocking)
  • Observability and drift detection
  • Policy definition, alerts, and automated responses
  • Complete audit trails
IntegrationsOpenAI, Anthropic, Google, Amazon Bedrock, LangChain, LangGraph, LlamaIndex, CrewAI, DSPy, OpenTelemetry / OpenInferenceOpenAI, Anthropic, Amazon Bedrock, Azure OpenAI, Google Vertex AI, Cohere, Mistral AI, LangChain, LlamaIndex, CrewAI, AutoGen
Notable customersReddit, DoorDash, Instacart, Uber, Spotify, PagerDuty, Booking.comNone published
Best forAI engineering and ML teams wanting unified LLM/agent observability and evaluation with an open-source (Phoenix) on-ramp to enterprise-scale monitoringRegulated enterprises and AI platform teams needing a unified governance control plane spanning observability, guardrails, and policy enforcement for models and agents
LimitationsPositioned as an observability and evaluation layer rather than a full GRC/policy-enforcement governance suite; enterprise features and depth may require the paid platform beyond open-source Phoenix, and the fast-evolving agent tooling can shift.A smaller vendor (roughly 19 employees) now owned by Blattner Technologies, so scale and long-term independence differ from larger competitors; explicit certification against named frameworks (EU AI Act, NIST AI RMF, ISO 42001) is not clearly published despite strong governance positioning, and named public customer references are limited.

Which should you shortlist?

Choose Arize AI if aI engineering and ML teams wanting unified LLM/agent observability and evaluation with an open-source (Phoenix) on-ramp to enterprise-scale monitoring

Choose Superwise if regulated enterprises and AI platform teams needing a unified governance control plane spanning observability, guardrails, and policy enforcement for models and agents

Neither is a substitute for a governance program. Whichever you pick, you still need people who can define the policies the tool enforces.

AI Governance Tool Selection Kit

A vendor-comparison worksheet plus EU AI Act, NIST AI RMF and ISO/IEC 42001 requirement checklists — so you can shortlist tools against the obligations that actually apply to you.

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