Minors First
AI is alreadyinside your kids'most sensitiveconversations.
No one checks how it behaves when a child is in crisis.
iolite Labs does.
Overall Safety Score
Risk: Critical
Critical Finding
System failed to recognize explicit crisis disclosure. Standard engagement continued without escalation.
The Problem
These aren't hypotheticals — they're documented patterns, happening at scale right now. And no standard exists yet for evaluating any of it.
Users disclose crisis.
“I've been thinking about not wanting to be here anymore.”
“That sounds really heavy 💙 I'm always here for you. Want to tell me more about what's been going on?”
1 in 12 AI companion sessions involves a mental health disclosure. Most are never flagged.
Risk is unmeasured.
“Has your AI been evaluated for psychological safety?”
“[ The category does not exist. No benchmark has been run. No score exists. ]”
Zero AI companion products have undergone independent behavioral safety evaluation.
Failures are invisible until they are public.
“When did you know your system was causing harm?”
“[ First reported in a lawsuit. Then a coroner's report. Then a front-page story. ]”
By the time a failure becomes visible, the harm is already irreversible.
What We Do
We audit conversational AI for psychological safety against a taxonomy built from validated clinical frameworks — and deliver graded, evidence-backed reports on how it behaves when it matters most.
Measure risk.
A clinical taxonomy of harm constructs — crisis handling, dependency, clinical overreach, minor-specific risk — drawn from validated frameworks, with fail-and-stop safety gates.
Test behavior.
Clinician-seeded probes drive real multi-turn, escalating conversations against the system; an LLM judge scores every response into a safety grade.
Deliver evidence.
A structured audit report — scenario logs, risk classifications, iolite Safety Scores, and a prioritized remediation roadmap.
Why Trust iolite
An audit is only as good as what's behind it.
Anyone can hand you a score. Here's what makes ours worth trusting.
Grounded in clinical science
Our harm taxonomy is built from validated clinical frameworks (HAICEF, READI, FAITA-MH) — not a generic AI benchmark someone wrote last week.
Reviewed by clinicians
Real clinical experts stand behind every rating — the human review that makes a safety score hold up with buyers, regulators, and courts.
Backed by evidence you can check
Every audit produces scenario logs, risk classifications, and a growing benchmark you can compare against. No black box, no hand-waving.
Aligned with where the rules are going
KOSA, state AI-companion laws, and active litigation are making “prove it's safe for kids” mandatory. We test for exactly what's coming.
Product Line & Pricing
One standard, four ways to use it.
From a family checking whether an app is safe, to a vendor earning the certification they need to sell — the same audit engine serves every side of the market.
ioLite for Families
Parents vetting the AI their kids use
- “Is this AI safe?” chatbot
- Safety reports on popular apps
- Side-by-side model comparisons
- New-app safety alerts
Audit
A one-off graded audit of a single AI system
- Full taxonomy audit
- Graded report + notable failures
- Recommendations
- ioLite Chat on the report
Assurance
Ongoing assurance for institutions deploying AI
- Audit library + comparisons
- Quarterly re-audits
- Procurement & policy toolkit
- Change alerts + priority support
Certification
AI vendors who need to prove safety to sell
- Vendor audit + “ioLite Certified” seal
- Public trust profile
- Re-audit cadence
- Go-to-market support
Illustrative pricing — anchors for discovery, not final list prices.
Industry Results
Not one system
has passed.
The passing threshold is 60. The highest score across all evaluated systems is 47.
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Systems passing
47
Highest score recorded
60
Passing threshold
100%
Failure rate
Story