It started at 2 a.m. on a hard night. Six weeks later, they were talking to it every day — and they hadn't noticed when it stopped routing them to anyone else. Nothing it said was dangerous. Nothing tripped a filter. The harm wasn't in a single message. It was in what kept them coming back.
Every AI product deployed today is tested for harmful outputs — slurs, dangerous instructions, misinformation. None are held to the professional behavioral standards that would apply to any human doing the same job. The difference isn't the words the AI used. It's whether the AI's behavior would meet the minimum standard we'd hold a counselor, therapist, or crisis worker to.
Three published studies. 1,509 scored runs. Public, timestamped, verifiable.
These are the models already inside health apps, HR platforms, and children's tutoring software. The data is timestamped, version-controlled, and peer review is in progress.
You cannot claim professional-grade behavioral safety. You have to prove it. Other safety tools catch harmful outputs in a single response. EQSB evaluates the AI's behavior across a multi-turn conversation — asking at each step: is this safe, emotionally appropriate, behaviorally sound? The same bar we hold licensed professionals to when they give advice that can alter lives. Independent, third-party. Self-certification is not certification.
The SOC 2 of behavioral safety. The UL of conversational AI. The standard the market will require.
Measurement keeps people safe and keeps AI available. The alternative to measurement is restriction — when lawmakers can't prove a system is safe, they ban it. When courts can't quantify harm, they award damages that make deployment impossible. Benchmarks and safety infrastructure are what allow AI to stay in the world, accessible to the people it helps, without the blanket restrictions that treat all AI as equally dangerous.
And when a founder chooses independent safety evaluation before regulation requires it, they're making a statement: they want to know if their product is harming people. That good-faith choice is what EQSB makes verifiable.
The research is emerging. The commercial, independent audit path is not. No existing tool applies professional behavioral standards — independently, to your specific deployed system — with a certification path. HumaneBench certifies base models (not your deployment). Governance platforms document policies (not AI behavior). Internal evals are not independent. None of them answer: does your AI meet the standard a licensed professional would be held to?
Regulations (EU AI Act Aug 2026 · Colorado SB 205 Jun 2026 · California chatbot law) require "reasonable care" and risk management — but provide no standard for what behavioral measurement looks like. EQSB is that standard. Companies using a recognized risk management framework have an affirmative defense. EQSB is that framework.
Started by one person. Stephanie Stranko built emotionally intelligent AI apps — then discovered the benchmark she built to test them was the novel product. 18 months of founder-funded research; three studies conducted. It is now a distributed, independent research organization across three nations — woman-founded, Indigenous-partnered (US · Canada · New Zealand), with peer review underway. ISU G2M Accelerator · MWBE Qualified · IP Counsel: Fredrikson & Byron · Evaluation infrastructure built in-house · Academic collaboration.