
Hailo AI
An edge AI processor technology that enables high-performance AI computing on edge devices with low power consumption.
Our take: Hailo is a hardware company that sells physical AI accelerator chips and modules (Hailo-8, Hailo-8L, Hailo-10H, Hailo-15) to OEMs, system integrators, and embedded developers through B2B and distributor channels.
The go-to edge AI chip for teams shipping real products that need on-device inference without cloud dependency.
Our score
Reviewed by the Conversion Gems editorial team. Hover a facet to focus it; click to pin.Tap a facet to focus it.
What it is, and why we rate it
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Our takeHailo is a hardware company that sells physical AI accelerator chips and modules (Hailo-8, Hailo-8L, Hailo-10H, Hailo-15) to OEMs, system integrators, and embedded developers through B2B and distributor channels.
Why we rate itHailo consistently delivers best-in-class TOPS-per-watt for edge AI.
The catchThis is a hardware play — you need the physical chip to do anything useful.
Best / not good for
- Embedded and hardware engineers building edge AI products (cameras, robots, ADAS)
- Raspberry Pi and hobbyist developers wanting affordable on-device AI inference
- OEMs and system integrators needing mass-production AI silicon with automotive/industrial grades
- Software-only teams without embedded hardware experience
- Cloud-first ML workloads where latency and data privacy are not constraints
- Startups needing a fully managed, no-hardware AI inference API
Friction report
Trade-offs to know before signing up.
- Time to valueModerate: Raspberry Pi HAT+ integration is quick for developers, but full OEM production design cycles (BSP, driver integration, model compilation) take weeks to months.
- Scale breakpointOEM volume ordering requires direct distributor or Hailo sales relationships; no self-serve bulk purchasing. Custom silicon supply chain timelines can become a bottleneck at scale.
- Walled gardenModerate: models must be compiled with Hailo's Dataflow Compiler and run via HailoRT — no drop-in ONNX/TFLite runtime. Migrating inference to a different chip requires re-compilation and testing.
A look inside

Frequently Asked Questions
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