How current AI security tools compare (and what’s missing)

We spent some time looking at existing AI security tools while building in this space.

There’s a lot of strong work already out there.

But when you look closely, most tools fall into a few patterns:

• Research-focused tools

→ powerful, but often complex and not built for everyday workflows

• Enterprise platforms

→ scalable, but usually tied to specific ecosystems

• Prompt-level testing tools

→ useful, but limited to surface-level checks

Each of these solves part of the problem.

But developers building AI agents today often need something simpler:

A way to test how their system behaves under adversarial input

before it goes live.

That’s where the gap starts to show.

Would love to hear how others are approaching this:

Are existing tools enough for your workflow,

or are you building custom testing setups?