Model monitoring companies, products & suppliers

Live watch on deployed model inputs, outputs and drift. Jobs: drift alerts; output monitors; performance by slice.

What is Model monitoring?

Live watch on deployed model inputs, outputs and drift. Jobs: drift alerts; output monitors; performance by slice.

What problems does it solve?

Production data shifts and nobody notices until users complain.

Typical business use cases

  • Drift alerts
  • Output monitors
  • Performance by slice

Important capabilities

  • Live metrics
  • Baselines
  • Alerting

What buyers should evaluate

  • What data is sampled
  • Alert routing
  • PII in samples

Risks and governance considerations

Sampled production records stored without a deletion story.

Procurement checklist

  • Sampling policy
  • Retention
  • On-call

Relevant AI Trustmark assurance

AI Trustmark independent findings appear only when an assessment or certificate exists. Category membership does not imply verification.

Methodology · How verification works

Products and providers

Open a product profile for its catalogue details, or use the provider link for the company profile. Claimed listings appear first, then by name. Payment never changes the order.

  • By AIMon

    AIMon is a Bessemer Ventures-backed company that helps you evaluate and improve RAG systems and LLM applications. AIMon is AIMon's platform, from AIMon Labs, Inc. Published at aimo

  • By Arize AI

    Continuously improve AI agents with agent observability, evaluation, tracing, and experimentation. Arize Model Monitoring is Arize AI's platform, from Arize AI, Inc. Published at a

  • By Censius

    Censius is an AI Observability Platform built for AI/ML teams to monitor, analyze, explain, and debug models. By flagging issues such as poor data quality, model drift, bias, and d

  • By Fiddler AI

    The AI Control Plane for enterprises. Gain visibility, context, and control through evaluation, monitoring, enforcement, governance, and cost efficiency. Fiddler AI Observability i

  • By Hydrosphere

    Hydrosphere is Hydrosphere's platform, from Hydrosphere.io, Inc. Published at docs.hydrosphere.io. Directory filing: Model monitoring. Vendor legal name on this product record: Hyd

  • By ModelFox

    ModelFox makes it easy to train, deploy, and monitor machine learning models. ModelFox is ModelFox's platform, from ModelFox, Inc. Published at modelfox.dev. Directory filing: Mode

  • By Mona

    Mona is Mona's platform, from Mona Labs Inc. Published at monalabs.io. Directory filing: Model monitoring. Vendor legal name on this product record: Mona Labs Inc. Mona is Mona's p

  • By Qualdo

    Qualdo™ helps you to monitor mission-critical data errors, drifts and quality in your favorite modern cloud databases & ML ecosystem. Try Qualdo today. Qualdo is Qualdo's platform,

  • By Sifflet

    Sifflet is the control plane for Data and AI. Catch data issues before they reach the business, trace them to root cause, and fix them fast. Trusted by Penguin Random House, Saint-

  • By Soda

    The AI-native, fully automated data quality platform. Find, understand and fix data quality issues in seconds with Soda. From table to record-level. NannyML Cloud is Soda's platfor

  • By SUPERWISE

    Control how AI is used across your company—so you can trust it. Complete visibility, guardrails, and control over AI usage. SUPERWISE Platform is SUPERWISE's platform, from Deep In

Products

Claimed products appear first. Ranking packs and payment do not change this list.

Also used in this category

These products have a different primary category so they do not compete for the same ranking queries. They are listed here because buyers still encounter them in this job.

Related categories

Relevant procurement and assurance guides

Frequently asked questions

What is Model monitoring?

Live watch on deployed model inputs, outputs and drift. Jobs: drift alerts; output monitors; performance by slice.

What should not be listed as Model monitoring?

Products whose buyer job is training-time experiment tracking, eval workbenches, or cost tools. Those belong on their own category page so search queries are not split.

Has AI Trustmark independently assessed every Model monitoring supplier?

No. A category listing is descriptive. Independent assessment is shown only on company or product pages that carry Trustmark evidence.

What logging should an AI agent provide?

Buyers should be able to see who the agent acted as, which tool was called, what data was sent, what changed, and when. Logs that omit write actions or store raw customer prompts without access control are incomplete evidence.

What model or provider changes should a buyer insist on being told about?

Material change usually includes a new model family, new region, new subprocessor, new write-capable tool, or a change that affects logging, privacy or human oversight. Those changes should trigger evidence refresh rather than a silent release.

How should buyers verify where AI customer data is processed?

Ask for the named processing locations, cloud regions and any subprocessors that see prompts, files or outputs. A directory listing is not evidence of residency. Independent assessment records the locations that were in scope on the assessment date.

Does a TrustMark on one product cover the rest of the company?

No. Independent assessment is scoped to the named organisation and, where relevant, the named product. Category pages list suppliers as a topic label. They do not imply that every listed company has been assessed.

What incident-handling evidence is useful for AI suppliers?

Buyers should see how AI-specific failures are detected, contained and notified — including unsafe outputs, data leakage and unauthorised agent actions. An incident policy that never mentions models, prompts or tools is incomplete for this class of product.