AI TrustMark

MLOps companies, products & suppliers

Operations for classical ML models: training, registry, deployment and monitoring. Jobs: model registry; deployment pipelines; feature/model lineage.

What is MLOps?

Operations for classical ML models: training, registry, deployment and monitoring. Jobs: model registry; deployment pipelines; feature/model lineage.

What problems does it solve?

Predictive models still ship from notebooks without a registry.

Typical business use cases

  • Model registry
  • Deployment pipelines
  • Feature/model lineage

Important capabilities

  • Registry
  • CI for models
  • Rollbacks

What buyers should evaluate

  • Reproducibility
  • Who can promote
  • Monitoring hooks

Risks and governance considerations

An undocumented model in production with no rollback.

Procurement checklist

  • Registry entry
  • Promotion rights
  • Rollback

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.

  • BentoML

    By BentoML

    Inference Platform built for speed and control. Deploy any model anywhere, with tailored inference optimization, efficient scaling, and streamlined operations. BentoML is BentoML's

  • Dagster

    By Dagster

    Dagster is a modern data orchestrator to build, schedule, and monitor reliable data pipelines for teams. Public marketing also emphasises software-defined assets approach. It is pr

  • MLflow

    By Databricks

    Databricks offers a unified platform for data, analytics and AI. Build better AI with a data-centric approach. Simplify ETL, data warehousing, governance and AI on the Data + AI Pl

  • dstack

    By dstack

    dstack is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters. dstack is dstack's platform, from dstack Gm

  • Get AI Ready Databricks AI consulting

    By Get AI Ready

    Get AI Ready is a UK Databricks-partner AI consulting arm delivering lakehouse, MLOps, agentic automation, and governance for enterprises. Public marketing also emphasises official

  • MLRun

    By Iguazio

    MLRun is Iguazio's platform, from Iguazio Ltd. Published at mlrun.org. Directory filing: MLOps. Vendor legal name on this product record: Iguazio Ltd. MLRun Iguazio Iguazio Ltd. ml

  • Infinite Lambda data & AI

    By Infinite Lambda

    Infinite Lambda is a data and AI consultancy specialising in modern data platforms (often Snowflake/dbt ecosystems) for UK/EU clients. Public marketing also emphasises modern data

  • KitOps

    By Jozu

    Jozu is the on-prem Kubernetes AI platform for secure model packaging, registry, and deployment. 7x faster with tamper-proof security. KitOps is Jozu's platform, from Jozu, Inc. Pu

  • Kedro

    By Linux Foundation

    Helping open technology projects build world class open source software, communities and companies. Kedro is Linux Foundation's platform, from The Linux Foundation. Published at ke

  • MindsDB

    By MindsDB

    MindsHub gives everyone the freedom to choose among leading AI models and providers—whether they use AI to get work done or build it into products. MindsDB is MindsDB's platform, f

  • Outerbounds / Metaflow

    By Outerbounds

    Outerbounds commercialises Metaflow infrastructure for building and operating real-life ML and AI systems. Public marketing also emphasises metaflow lineage from Netflix. It is pre

  • Prefect

    By Prefect

    Prefect is a workflow orchestration platform for data and ML pipelines with a modern Pythonic developer experience. Public marketing also emphasises pythonic workflow orchestration

  • Seldon Core 2

    By Seldon

    Real-time machine learning deployment with enhanced observability for any AI application or system, managed your way. Seldon Core 2 is Seldon's platform, from Seldon Technologies L

  • TrueFoundry

    By TrueFoundry

    TrueFoundry markets an AI gateway and MLOps platform for deploying and governing models and LLM apps in enterprise environments. Public marketing also emphasises aI gateway + MLOps

  • Union

    By Union.ai

    One platform to orchestrate durable AI workflows, real-time apps, and compute optimization. Your data never leaves your infrastructure. Union is Union.ai's platform, from Union Sys

  • W&B Experiments

    By Weights & Biases

    Learn why thousands of companies rely on W&B as their system of record for training AI models and developing AI applications with confidence. W&B Experiments is Weights & Biases's

  • ZenML

    By ZenML

    ZenML Labs is the unified infrastructure layer for AI in production: ZenML orchestrates your pipelines and agents on the infra you choose, and Kitaru replays them on production dat

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 MLOps?

Operations for classical ML models: training, registry, deployment and monitoring. Jobs: model registry; deployment pipelines; feature/model lineage.

What should not be listed as MLOps?

Products whose buyer job is LLMOps, experiment trackers alone, or AutoML products. Those belong on their own category page so search queries are not split.

Has AI Trustmark independently assessed every MLOps 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.