The Next Great
AI Platform Battle
Is Vision

See who’s winning the race to become the platform layer for visual intelligence.

The number of AI Vision platforms has suddenly doubled
‍– you should know why.
The bottleneck has moved. Models are no longer what limits
AI Vision performance.
AI vision is entering a new era of innovation, with platforms
opening the door.

WHAT'S INCLUDED

Benchmark rankings

PDF

The ranking prompt

And the Executive summaries for Integrators · Business Leaders · Developers

Qualcomm Dragonwing IQ-30175 EVK small electronic development board with various ports and slots.

GET THE WHITE PAPER FOR FREE

This is for you if...

INTEGRATORS & PARTNERS

You want to add AI video to what you already sell and install

What the shift to platforms means for what you sell and install — which layer to align with, and what to ask a vendor before you commit.

BUSINESS LEADERS

You want more out of the cameras you already have

Where AI video analytics pays off on video or cameras you already own, and what separates a project that ships from one that stalls.

DEVELOPERS

You want to ship vision apps without building the platform

The twelve attributes in brief, why each one matters once an application is in production, and how thirty-five platforms scored against them.

Why most AI vision projects stall before production

Vision‑language models got better. The failure rate barely moved.

LLMs and open‑vocabulary detection crossed into commercial usefulness. Yet most AI video analytics projects — in security, retail and manufacturing alike — still die before production. Nobody had written down what an AI vision platform has to do to survive it, or who is doing it well.

80–90% of models

still never reach production

$3.9 billion

paid for a software abstraction layer

3-12 months from concept to Production

Building AI vision from scratch takes more work than most teams expect

How we scored 35
AI vision platforms

1
Twelve attributes, four questions
How an AI vision application is built, where it runs, who can use it, and whether it survives production at scale.
2
Public evidence only
A fixed 0–3 rubric. Vendor documentation outranks press, and undocumented capability scores as absent.
3
A prompt, not an opinion
The research was run by a published prompt, so anyone can regenerate the table or argue with it on the evidence.