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Machine Learning · head to head

ClearML vs Veritone

ClearML logo

ClearML

Machine Learning

Open-source MLOps platform for experiment tracking and orchestration

From
Free
Free plan
Yes
Full reviewWebsite
Veritone logo

Veritone

AI

AI orchestration platform and applications for media archives, public safety evidence and advertising

From
On request
Free plan
No
Full reviewWebsite

The short version

  • Only ClearML has a free tier, so it costs nothing to try first.
  • Each has a real cost: ClearML broad scope means more to learn and more to run than a focused tracking tool; Veritone nothing is publicly priced, and because consumption of the underlying AI engines is metered, the total cost of a large archive ingest is difficult to forecast before you have run one.
  • They diverge on capability: ClearML covers Experiment tracking, Veritone covers aiWARE orchestration.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which ClearML and Veritone actually diverge.

Attributes where ClearML and Veritone differ
AttributeClearMLVeritone
Starting priceFreeOn request
Pricing modelOpen-source self-hosted, with paid hosted and enterprise tiersquote
Free tierYesNo
PlatformsLinux, macOS, Windows, Docker, KubernetesWeb, API, Self-hosted
CategoryMachine LearningAI

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 ClearML

  • Experiment tracking
  • Remote execution
  • Data versioning
  • Pipelines

Only in Veritone

  • aiWARE orchestration
  • iDEMS
  • Automated redaction
  • Media archive indexing
  • FedRAMP authorisation
  • Advertising and content intelligence
  • Voice and synthetic media
  • Self-hosted deployment

What people use each for

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

ClearML

  • Tracking experiments across a team so results are reproduciblenot Veritone
  • Moving training from laptops to shared GPU hardware without repackagingnot Veritone
  • Versioning datasets alongside the experiments that consumed themnot Veritone

Veritone

  • A police department buried in body camera footage that must be redacted before disclosure, where automated face and audio redaction converts weeks of manual work into review timenot ClearML
  • A broadcaster or sports rights holder that cannot find footage in its own archive and loses licensing revenue because searching it costs more than the clip earnsnot ClearML
  • A federal agency that needs AI processing inside an authorised boundary, where FedRAMP status decides the shortlist before capability doesnot ClearML
  • A media buyer wanting attribution on broadcast and podcast advertising that digital analytics tools cannot seenot ClearML

Where each one falls short

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

ClearML

  • Broad scope means more to learn and more to run than a focused tracking tool
  • Self-hosting the server is real infrastructure — database, file storage and web server
  • Documentation quality is uneven across the newer parts of the platform
  • Smaller community than the most popular tracking tools, so fewer worked examples exist

Veritone

  • Nothing is publicly priced, and because consumption of the underlying AI engines is metered, the total cost of a large archive ingest is difficult to forecast before you have run one.
  • The company is mid-restructure after divesting its media agency, with revenue guidance well below earlier expectations, so a buyer signing a multi-year evidence contract is taking corporate risk they can read in the public filings but cannot control.
  • The orchestration proposition means Veritone sits between you and the model vendors, so when a specific engine underperforms on your content the remedy is a support case rather than switching provider yourself.
  • The product portfolio spans law enforcement, broadcast, advertising and synthetic voice, which is a wide surface for one engineering organisation and means attention to any single application depends on where the revenue growth currently is.
  • Automated redaction is a review aid, not a guarantee: an agency remains legally responsible for what is disclosed, so the staff time saved is smaller than the demonstration implies once verification is included.

Pricing, plan by plan

ClearML

Free
  • Open sourceFree
    • Experiment tracking
    • Pipelines
    • Self-hosted server

Veritone

On request
  • aiWARE platform$undefined/year
    • Consumption-based use of the AI engine catalogue
    • Enterprise licence, quoted
    • Self-hosted and FedRAMP deployment options
  • iDEMS$undefined/year
    • Digital evidence management for law enforcement
    • Automated redaction and disclosure workflow
    • Quoted per agency, commonly on government contract vehicles
  • Media and entertainment applications$undefined/year
    • Archive indexing, monetisation and advertising intelligence
    • Quoted

Which should you pick?

Choose ClearML if

  • You need experiment tracking.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Kubernetes.
  • You also want remote execution.
ClearML review

Choose Veritone if

  • You need aiware orchestration.
  • You work on Web, API, Self-hosted.
  • You also want idems.
Veritone review

Questions people ask

Is ClearML or Veritone better?
Neither clearly leads. ClearML starts at Free and Veritone at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, ClearML or Veritone?
ClearML has a free tier; the other does not. Paid plans start at Free for ClearML and On request for Veritone.
Does ClearML or Veritone run on more platforms?
ClearML runs on Linux, macOS, Windows, Docker, Kubernetes. Veritone runs on Web, API, Self-hosted.
Can I use ClearML for free?
Yes. ClearML has a free tier, so you can try it without paying. Veritone starts at On request.
What is ClearML best used for?
ClearML is most often used for tracking experiments across a team so results are reproducible, moving training from laptops to shared gpu hardware without repackaging, versioning datasets alongside the experiments that consumed them. Of those, tracking experiments across a team so results are reproducible and moving training from laptops to shared gpu hardware without repackaging are not what Veritone is typically brought in for.
What can ClearML do that Veritone cannot?
ClearML covers Experiment tracking, Remote execution, Data versioning, Pipelines. Veritone covers aiWARE orchestration, iDEMS, Automated redaction, Media archive indexing.

Answered from the vendors’ own pages

ClearML: Is ClearML free?

The open-source version is free and self-hostable. Hosted and enterprise tiers are paid.

Veritone: What do you actually buy from Veritone?

An application, most often iDEMS for digital evidence or a media archive product. aiWARE is the platform underneath, and it is rarely purchased on its own outside enterprise and government deals.

ClearML: How much code does tracking require?

Very little — adding a couple of lines to an existing training script captures parameters, metrics and environment automatically.

Veritone: Is pricing published?

No. Everything is quoted, and platform use is metered by consumption of the underlying AI engines, which makes forecasting a large ingest difficult.

ClearML: Does ClearML replace MLflow?

It covers MLflow’s tracking and adds orchestration, remote execution and data versioning. Whether that breadth is an advantage or extra weight depends on whether you need the rest.

Veritone: Is it approved for US government use?

aiWARE holds FedRAMP authorisation and can be deployed into self-hosted government tenants, which is frequently the reason it reaches a public sector shortlist.

Veritone: Did Veritone sell its advertising agency?

Yes. Veritone One was divested in 2024 for up to $104 million, and the remaining company is focused on enterprise AI software and licensing.

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