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AI · head to head

Arize AI vs Seldon

Arize AI logo

Arize AI

AI

AI engineering platform for observability and evaluation of agents and LLM apps

From
Free
Free plan
Yes
Seldon logo

Seldon

Machine Learning

Kubernetes model serving whose current version is licensed under the Business Source Licence

From
Free
Free plan
Yes

The short version

  • Each has a real cost: Arize AI the free plan caps trace spans at 25,000 per month with only 15 days of retention.; Seldon seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • They diverge on capability: Arize AI covers End-to-end tracing, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Arize AI and Seldon actually diverge.

Attributes where Arize AI and Seldon differ
AttributeArize AISeldon
Platformsweb, apiLinux
CategoryAIMachine Learning
FoundedUnknown2014

Identical on both: starting price (Free), pricing model (freemium), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Arize AI

  • End-to-end tracing
  • Evaluation framework
  • Prompt testing and improvement
  • Alyx AI engineering agent
  • Custom dashboards
  • Data warehouse integrations

Only in Seldon

  • Kubernetes custom resources
  • Inference graphs
  • Traffic strategies
  • Open Inference Protocol
  • Alibi Explain
  • Alibi Detect
  • Kafka-backed pipelines in v2
  • Commercial control plane

What people use each for

The jobs each tool is most often brought in to do.

Arize AI

  • Tracing and debugging production AI agentsnot Seldon
  • Running large-scale evaluations across traces and sessionsnot Seldon
  • Improving prompts before production rolloutnot Seldon
  • Storing and querying GenAI traces alongside a data warehousenot Seldon

Seldon

  • Serving an ensemble or a multi-stage inference path as one versioned deployment rather than as a chain of separate servicesnot Arize AI
  • Running genuine production experiments where a share of live traffic goes to a candidate model and the results are comparednot Arize AI
  • Regulated environments needing explanations and drift monitoring attached to the served model rather than bolted on laternot Arize AI
  • Organisations with an established Kubernetes platform team who want serving expressed as manifests under existing deployment controlsnot Arize AI

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Arize AI

  • The free plan caps trace spans at 25,000 per month with only 15 days of retention.
  • Self-hosted deployment and Data Fabric integration are restricted to the custom-priced Enterprise tier.
  • Pricing beyond the $50/month Pro plan requires a custom quote, making cost planning less transparent at scale.
  • Advanced compliance features like HIPAA are only available on Enterprise.

Seldon

  • Seldon Core v2 is under the Business Source Licence rather than Apache 2.0, so production use requires a commercial agreement, and a team that evaluated it believing it was open source discovers the licence is the blocker exactly when the project is ready to ship.
  • Core v1 remains Apache 2.0 but is in maintenance, so taking the free route means running software that receives no new development while the architecture it belongs to moves on without it.
  • Version 2 is a different system rather than a newer release, with different custom resources, a scheduler component and a Kafka-based pipeline model, so migrating from v1 is a re-implementation of every deployment manifest rather than an upgrade.
  • Kafka is a dependency for v2 pipelines, so an organisation that does not already operate it takes on a distributed log with its own storage, retention, rebalancing and failure modes purely in order to serve models.
  • Everything assumes Kubernetes fluency and the failure modes are Kubernetes failure modes, custom resource version mismatches, an operator that will not reconcile, admission webhooks and resource limits terminating an inference pod mid-request, so it needs a platform engineer rather than a data scientist.

Pricing, plan by plan

Arize AI

Free
  • AX FreeFree
    • 25k trace spans/month
    • 1 GB storage/month
    • 15-day retention
  • AX Pro$50/month
    • 50k trace spans/month
    • 10 GB storage/month
    • 30-day retention
  • AX Enterprise$undefined/mo
    • Custom trace spans, storage, and retention
    • SaaS or self-hosted deployment
    • Managed agents and Data Fabric

Seldon

Free
  • Seldon CoreFree
    • Open source
    • Kubernetes deployment
    • Model serving
  • Seldon DeployFree
    • Enterprise features
    • GUI
    • Monitoring

Which should you pick?

Choose Arize AI if

  • You need end-to-end tracing.
  • You want to start without paying.
  • You work on web, api.
  • You also want evaluation framework.

Choose Seldon if

  • You need kubernetes custom resources.
  • You want to start without paying.
  • You work on Linux.
  • You also want inference graphs.

Questions people ask

Is Arize AI or Seldon better?
Neither clearly leads. Arize AI starts at Free and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Arize AI or Seldon?
Arize AI starts at Free and Seldon at Free.
Does Arize AI or Seldon run on more platforms?
Arize AI runs on web, api. Seldon runs on Linux.
Can I use Arize AI for free?
Both have a free tier, so you can try either at no cost before committing.
What is Arize AI best used for?
Arize AI is most often used for tracing and debugging production ai agents, running large-scale evaluations across traces and sessions, improving prompts before production rollout, storing and querying genai traces alongside a data warehouse. Of those, tracing and debugging production ai agents and running large-scale evaluations across traces and sessions are not what Seldon is typically brought in for.
What can Arize AI do that Seldon cannot?
Arize AI covers End-to-end tracing, Evaluation framework, Prompt testing and improvement, Alyx AI engineering agent. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Arize AI: What does Arize AX cost?

Arize AX offers a free plan, a Pro plan at $50/month, and a custom-priced Enterprise plan, with pricing based on trace spans, storage, and retention needs.

Source
Seldon: Is Seldon open source?

Partly, and this is the thing to check before you build on it. Core v1 is Apache 2.0 but in maintenance. Core v2 was moved to the Business Source Licence in 2024, which allows evaluation but not unlicensed production use. Verify the current licence of each component you intend to run, including MLServer and the Alibi libraries.

Arize AI: Is there a free plan, and what are its limits?

The AX Free plan includes 25,000 trace spans and 1 GB of storage per month with 15-day retention, plus unlimited users, evaluations, and experiments.

Source
Seldon: What is the difference between v1 and v2?

Architecture, not just version number. v2 introduces a scheduler, a different set of custom resources and Kafka-backed pipelines. Manifests, mental model and operations all change, so treat a move as a project.

Arize AI: What deployment options are available?

Free and Pro plans are SaaS-only, while Enterprise customers can choose SaaS or self-hosted deployment with custom SLAs.

Source
Seldon: Do I need Kubernetes?

Yes. It is a Kubernetes-native system and there is no meaningful deployment without a cluster and someone competent to run it.

Seldon: What is MLServer?

Seldon's Python inference server implementing the Open Inference Protocol, usable inside Seldon deployments or on its own. Check its current licence alongside Core's, since the company has moved projects onto the Business Source Licence.

Seldon: Do I have to run Kafka?

For v2 pipelines, yes. If you only need single models served, that dependency is a large amount of infrastructure for the benefit, and a simpler serving layer may be the better answer.

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