CONSUMER AI TRUST
AI your customers can trust.
The assistant, the coach, the support agent, the recommender: when AI faces your customers, every answer is a brand promise, and the bad one gets screenshotted. Trust is an engineering outcome. We define what on-brand and safe mean for your product, test it the way the internet will, and watch it in the wild.
THE SURFACE
Your AI is your brand now, one answer at a time.
Customers experience your AI the way they experience your best employee: they take its word, repeat its promises, and remember how it made them feel. An invented policy, an off-tone reply, a mishandled sensitive moment, each one is a customer interaction your brand has to own. The failure mode is public by default: one AI support bot's invented login policy went viral and cost its company cancellations, a national chain publicly rethought its drive-through voice AI after a prank order spread, and only 13 percent of consumers say they completely trust AI. The companies that win with consumer AI treat its behavior as a product surface with a quality bar, engineered and measured like one.
ENGINEERED TRUST
Taste, encoded as evals.
Generic safety checks are the easy part, and they come standard. The hard part is your standard: what a good answer sounds like in your brand voice, which promises the AI may make, where it must hand off to a human, and how it handles the moments that matter most, from a frustrated customer to a crisis disclosure. We encode that judgment into custom evals, red-team the product the way real users and trolls will push on it, and prove it passes before your customers meet it.
IN THE WILD
Trust holds because someone is watching.
Launch is where the real test starts. Monitoring watches quality across live conversations, catches drift as models and usage change, and feeds what production teaches back into the standard. We have shipped consumer AI at scale, including a voice coach serving 175,000+ language learners, and the pattern holds: the products that keep trust are the ones that keep proving it. If children use your product, that is its own discipline: child-safe AI.
COMMON QUESTIONS
Asked by brand owners, answered plainly.
Is 99 percent accuracy good enough?
Do the volume math: at a million interactions a year, 99 percent right means ten thousand wrong, and the wrong ones get screenshotted. The work is knowing which one percent you can live with, engineering toward the harmless kinds, and catching the harmful kinds before customers do.
Customers say they prefer humans. Should we even ship AI support?
Preference follows performance: most consumers distrust AI support because most AI support is generic, and only 13 percent say they completely trust AI. Trust is engineered per moment: clear handoffs where judgment matters, transparency about what they are talking to, and evals that encode your standard for every answer.
How do you handle the sensitive moments: health, money, crisis?
As named, tested behaviors: safe-messaging playbooks, mandatory handoffs, and evals that verify the system does the right thing under pressure, including breaking script to surface help at exactly the right moment.
What does on-brand even mean as a test?
Your taste, encoded: the tone, the promises the AI may and may not make, the moments it must escalate. We turn that judgment into custom evals, so on-brand stops being a vibe and becomes a bar the system provably clears.
LET'S TALK
Bring us the hard problem.
We'll bring the team that ships.