AI TrustMark

Embedded AI companies, products & suppliers

Models on microcontrollers and deeply embedded hardware, not edge servers or wearable apps. Jobs: tinyml; sensor on-chip inference; mcu toolchains.

What is Embedded AI?

Models on microcontrollers and deeply embedded hardware, not edge servers or wearable apps. Jobs: tinyml; sensor on-chip inference; mcu toolchains.

What problems does it solve?

MCUs still cannot run a useful model within power and RAM.

Typical business use cases

  • TinyML
  • Sensor on-chip inference
  • MCU toolchains

Important capabilities

  • Power
  • RAM
  • Toolchain

What buyers should evaluate

  • Power budget
  • Update path
  • Whether it needs a cloud

Risks and governance considerations

A 'tiny' model that phones home continuously.

Procurement checklist

  • Power
  • Cloud or not
  • Update

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.

  • AWS IoT Greengrass

    By Amazon Web Services

    AWS IoT Greengrass is an open-source edge runtime and AWS cloud service for building, deploying and managing software on IoT devices. Developers assemble device software from prebu

  • Ambarella CV3

    By Ambarella

    Ambarella CV3-AD is an ASIL B(D)-compliant AI domain controller system-on-chip family for multi-sensor perception, fusion and path planning in L2+ to L4 autonomous driving and prem

  • Core ML

    By Apple

    Core ML is Apple's on-device machine learning framework for integrating trained models into apps on Apple platforms. Developers can run vision, natural language and other ML models

  • Metis AIPU

    By Axelera AI

    Bring data insights to the edge, increasing the performance of your solutions with a cost-effective and efficient inference chip. Axelera’s AI processing unit is designed to seamle

  • Google Coral

    By Google

    Coral is Google's full-stack platform for edge AI, combining an AI-first, standards-based hardware architecture with a unified developer toolchain so AI can run locally on devices.

  • Hailo-10

    By Hailo

    Explore Hailo’s AI chip for AI on the edge. Use the best-tailored high-performance AI processors for edge device solutions. Hailo-10 is Hailo's hardware product, from Hailo Technol

  • Jetson AGX Orin Industrial module

    By NVIDIA

    Jetson AGX Orin Industrial is the ruggedised production module in NVIDIA's Jetson AGX Orin series, built for edge AI and robotics products that need industrial-grade hardware. It d

  • Edge Impulse

    By Qualcomm

    Edge Impulse, a Qualcomm company, is an MLOps platform for edge and physical AI. It provides end-to-end pipelines for collecting sensor data, building, versioning, securing and mon

  • SiMa.ai Modalix

    By SiMa.ai

    SiMa.ai scaling physical ai across across robotics, automotive, industrial automation, aerospace & defense, smart vision, and healthcare. SiMa.ai Modalix is SiMa.ai's hardware prod

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 Embedded AI?

Models on microcontrollers and deeply embedded hardware, not edge servers or wearable apps. Jobs: tinyml; sensor on-chip inference; mcu toolchains.

What should not be listed as Embedded AI?

Products whose buyer job is edge inference, wearable AI, or on-device assistants. Those belong on their own category page so search queries are not split.

Has AI Trustmark independently assessed every Embedded AI supplier?

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

What security testing evidence should buyers request for an AI product?

Ask what was tested, against which version, whether prompt-injection, data-exfiltration and tenant isolation were in scope, and where failed prompts were stored. A generic ISO certificate or a vendor scanner screenshot is not by itself an AI TrustMark assessment.