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AI · head to head

Avathon vs Seldon

Avathon logo

Avathon

AI

Industrial AI for asset performance and renewables, formerly SparkCognition

From
On request
Free plan
No
Full reviewWebsite
Seldon logo

Seldon

Machine Learning

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

From
Free
Free plan
Yes
Full reviewWebsite

The short version

  • Only Seldon has a free tier, so it costs nothing to try first.
  • Each has a real cost: Avathon the company rebranded from SparkCognition to Avathon and narrowed its focus after repeated reported layoff rounds, so reference checks and roadmap commitments made under the old name need reconfirming.; 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: Avathon covers Renewable Suite, Seldon covers Kubernetes custom resources.
  • Prices and features above were last checked on 1 September 2026.

Where they differ

Only the attributes on which Avathon and Seldon actually diverge.

Attributes where Avathon and Seldon differ
AttributeAvathonSeldon
Starting priceOn requestFree
Pricing modelquotefreemium
Free tierNoYes
PlatformsWeb, CloudLinux
CategoryAIMachine Learning
FoundedUnknown2014

Identical on both: 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 Avathon

  • Renewable Suite
  • Loss attribution
  • Predictive maintenance models
  • Computer vision
  • Digital twin models
  • Work order integration
  • Fleet benchmarking
  • Document intelligence

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.

Avathon

  • A wind fleet owner wanting underperforming turbines ranked by lost megawatt hours rather than by alarm countnot Seldon
  • A solar independent power producer detecting inverter and string underperformance that falls below the SCADA alarm thresholdnot Seldon
  • A manufacturer with years of historian data and failure records who wants failure prediction models trained on their own historynot Seldon
  • A site using cameras to detect missing personal protective equipment or unauthorised entry into restricted zonesnot Seldon

Seldon

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

Where each one falls short

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

Avathon

  • The company rebranded from SparkCognition to Avathon and narrowed its focus after repeated reported layoff rounds, so reference checks and roadmap commitments made under the old name need reconfirming.
  • Headcount is in the low hundreds against a product portfolio spanning renewables, vision, predictive maintenance and document AI, which is thin coverage per product line for enterprise support expectations.
  • Model accuracy depends on having enough labelled historical failures, and sites with short data history or poor maintenance record-keeping get generic anomaly detection rather than useful failure prediction.
  • Nothing is published about pricing or asset-count thresholds, so there is no way to judge whether a small fleet is even a viable customer without entering a sales cycle.
  • It sits on top of your SCADA and CMMS rather than replacing them, so the integration and asset-hierarchy mapping work is a real project cost that the software subscription does not cover.

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

Avathon

On request
  • Avathon$undefined/year
    • Annual subscription sized by asset count or installed megawatts for renewables
    • Separate pricing for vision, predictive maintenance and document products
    • Model development and data onboarding quoted as a professional services project

Seldon

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

Which should you pick?

Choose Avathon if

  • You need renewable suite.
  • You work on Web, Cloud.
  • You also want loss attribution.
Avathon review

Choose Seldon if

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

Questions people ask

Is Avathon or Seldon better?
Neither clearly leads. Avathon starts at On request and Seldon at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Avathon or Seldon?
Seldon has a free tier; the other does not. Paid plans start at On request for Avathon and Free for Seldon.
Does Avathon or Seldon run on more platforms?
Avathon runs on Web, Cloud. Seldon runs on Linux.
Can I use Seldon for free?
Yes. Seldon has a free tier, so you can try it without paying. Avathon starts at On request.
What is Avathon best used for?
Avathon is most often used for a wind fleet owner wanting underperforming turbines ranked by lost megawatt hours rather than by alarm count, a solar independent power producer detecting inverter and string underperformance that falls below the scada alarm threshold, a manufacturer with years of historian data and failure records who wants failure prediction models trained on their own history, a site using cameras to detect missing personal protective equipment or unauthorised entry into restricted zones. Of those, a wind fleet owner wanting underperforming turbines ranked by lost megawatt hours rather than by alarm count and a solar independent power producer detecting inverter and string underperformance that falls below the scada alarm threshold are not what Seldon is typically brought in for.
What can Avathon do that Seldon cannot?
Avathon covers Renewable Suite, Loss attribution, Predictive maintenance models, Computer vision. Seldon covers Kubernetes custom resources, Inference graphs, Traffic strategies, Open Inference Protocol.

Answered from the vendors’ own pages

Avathon: Is this the same company as SparkCognition?

Yes. SparkCognition rebranded to Avathon and refocused on industrial and government asset AI.

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.

Avathon: Which product is most mature?

The renewable energy suite for wind and solar underperformance, which has the longest production deployment history.

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.

Avathon: Does it need my historian data in the cloud?

Generally yes for model training and ongoing scoring, which is a security review item for utility and defence customers.

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.

Avathon: Can it work without historical failure records?

It will still do anomaly detection, but failure prediction models need labelled historical failures to be worth the deployment cost.

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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