Where trust in a model decides whether it ships.
The same question comes up in every field: what did the model rely on, can we change it safely, and will it hold? Here is where Inverse AI starts, and where it goes next.
Medical imaging
“Did the model grade the retina, or the camera’s dark border?”
- Explanations scored inside the anatomy that can carry evidence
- Comparison of explanation methods per image and per grade
- A per-image report a clinician can review
Starting point: diabetic retinopathy (Sight). A research study, not a medical device; any clinical use would need its own validation and regulatory approval.
Language-model safety and alignment
“We steered the model to be more careful. Did it work, compared with what, and what did it cost?”
- STEER cards for every intervention
- Evaluation against strong baselines, not just the untouched model
- Capability and compute cost reported with each gain
Vision-language models
“Does a change made for text still hold when the model also sees?”
- One evaluation standard for text-only and vision-language models
- Explicit labels where a result is untested in one modality
- Image-side explanations checked the same way as in Sight
Regulated decisions
“Can we show an auditor why this decision was made, and that the model hasn’t drifted since?”
- Decision reports pairing each output with checked explanations
- Explanation drift and fairness monitoring
- An audit trail aligned with high-risk AI obligations
Built in the UAE, for teams adopting AI quickly.
The UAE and the wider Gulf are adopting AI across government, healthcare, and finance. Fast adoption needs independent evaluation alongside it.
Independent evaluation
Explanation and intervention audits for models before and after deployment.
Research partnership
Joint studies with universities and hospitals, grounded in work done at UAEU.
Capability building
Training for teams who need to read, question, and act on model explanations. Our founder has run AI workshops for educators and parents in the UAE since 2020.
Is your use case missing?
Tell us what model you need to trust and why. Early partners shape what we build first.