MirageLabs
Robustness testing for the AI systems the world runs on. We find where perception, detection, and autonomy break.
The world is moving to secure LLMs. But the models steering perception, detection, and autonomy often go untested. We test those.
Explain. Exploit. Protect.
Explain
See how a model decides, and where it leans on the wrong signal.
Exploit
The Mirage platform attacks your model like a malicious cyber actor would. Gradient, physical, black box. Prove every failure.
Protect
Turn failures into defenses that hold, from adversarial training to certified robustness.
A few bits is all it takes
A perturbation too small to notice flips a confident prediction. It works on pixels, on sound, on network traffic. It never shows up in an accuracy score. It is the first thing we look for.
A 3D world built to break your autonomy stack
Give us your model. We rebuild the environment it operates in, run it inside, and hunt for the conditions that make it fail.
Any model, any environment. Drop in a perception or planning model. We render the scene from every angle, altitude, light and weather state, and score it at each one.
Only scenarios a real sensor could encounter make the list. You get back a ranked set of the conditions that break your stack, each one reproducible in your own simulator.
Robotics & autonomy
Perception and planning stacks in vehicles, drones, and robots fail in ways that never appear in an accuracy benchmark. We test the inputs that actually break them.
Risk-ranked scenario search instead of uniform coverage, so every hour you drive is one the model might actually fail.
Some things our platform has fooled
Watch it break a live model
Real attacks across vision, audio, text, and network models. No setup. See exactly where a model fails, and by how much.
Talk to us
Book a demo, or tell us where you need to be more resilient.