Defensibility infrastructure
Law enforcement, national security, and regulated institutions are accountable for what their AI produces. AINA builds the infrastructure that lets AI meet that standard — traceable to source, explainable on demand, defensible under challenge.
The condition
The institutions that most need deliberate AI are the ones held most accountable for what it produces.
These buyers are increasingly required — by statute, by procurement, by the courtroom — to use AI whose outputs can be explained, traced, and defended under adversarial review.
General-purpose models were not built to meet that bar. The distance between what these institutions must have and what the market hands them is widening, not closing — and no amount of accuracy alone resolves it.
AINA's system · ROSSO
A defensibility architecture, not another model.
ROSSO is the system AINA builds. It is domain-agnostic by design: it surfaces source-anchored indicators for a person to weigh — it does not score, threshold, or decide. Every indicator carries its provenance, so any output can be traced back to the record it came from.
First domain
Trafficking is where the architecture proves out — not what it's for.
AINA's first domain is human trafficking, chosen for technical tractability — anchored in a stable federal legal framework — and for a market shaped by clear mandates, funding, and compliance pressure.
The architecture is not built for one mission. Trafficking is the first proving ground for a capability that institutions across high-accountability settings will need.
Validation
Team
Kimberly Adams
Co-founder & CEO
Columbia-educated. Has driven AINA from concept through validation across five years.
Shweta Jain
Co-founder & Technical Architect
Chair of Mathematics and Computer Science, John Jay College. Leads ROSSO's technical design.