Customer-facing AI assistants
Support, onboarding, self-service.
The version of customer-facing AI that gets the worst reputation is the one that shows up on a site, greets you with a bubble, asks what you need, and then hands you straight back to a form because it cannot actually help. Users click around it, find the email address, and send a ticket anyway.
Done right, AI on the customer side is not a replacement for support. It is a filter.
About sixty percent of tickets in most businesses are the same handful of questions asked in different ways. “How do I reset my password.” “Where is my order.” “Why was I charged twice.” “Can I cancel.” A good AI assistant answers those in the user's own words, at three in the morning, in the language they wrote in, without the user having to search a help center. The team then gets to spend their day on the other forty percent that actually needs a human.
The hard part is not the language model. The hard part is making sure the assistant knows what is true about your product today, not what was true six months ago when someone last edited the help center. That's where most projects quietly fail.
What we do here:
- Start with a week of real tickets and find the top ten questions they actually cluster into.
- Ground the assistant in your live content: product docs, order data, account state, pricing. No hallucinating policies.
- Give it a clear handoff to a human when it's not confident, with the full conversation attached.
- Measure deflection honestly, by resolved tickets, not by vanity engagement numbers.
- Keep an eye on tone: the assistant should sound like your brand, not like a generic chatbot pretending to be a person.
The bar is simple. If the assistant makes life easier for the customer and lighter for the support team, it stays. If either of those is not true, we fix it or turn it off.