Slow support costs you customers long before bad support does. We build AI that drafts email and chat replies from your own knowledge base, answers the repeat questions itself, summarises calls, and routes incoming documents — while a person still owns anything sensitive. Not a demo, a system already running for a major airline.
In support, speed is the product. An answer that arrives after the customer has given up — missed the flight, cancelled the order, left the review — isn't support any more; it's damage control.
But fast and wrong is worse than slow. So we build for both. The AI answers in minutes from your own knowledge base, knows who the customer is through your CRM, and hands anything sensitive — money, cancellations, account changes — to a person before it goes out. It's allowed to be fast only where being wrong is cheap.
The result is a desk that keeps up without losing the judgement your customers actually notice.
Proof beats promises. Here's one running for real, right now.
Passengers were emailing to change flights, move payments or ask for help — and answers arrived after the flight had already left. We wired an AI agent into the support inbox and the airline's CRM: it reads each message, knows whether the sender is a ticketed passenger and when they fly, and drafts a reply in minutes. Anything touching money waits for a human.
It started on a single route alongside human reps, then expanded across destinations, international flights, and finally the premium cabins — where a passenger must never feel they're talking to a machine. Read the full case →
Built into the channels and tools your team already uses, not a separate box to babysit.
Incoming messages read and answered from your own knowledge base — sent automatically where it's safe, or drafted for a one-click human approval where it isn't. Consistent, on-brand, and grounded in what your docs actually say.
A chatbot on your site or in-app that answers from your own content, deflecting the repeat questions before they ever become a ticket — and handing off cleanly to a person when it should.
Calls transcribed and summarised into a tidy record: what was asked, what was decided, the action items, logged straight to the ticket or CRM so nobody re-types a conversation.
Attachments that arrive with a request — forms, receipts, IDs, contracts — read, classified, and matched to the right customer, ticket or case, so the right file lands in the right place without manual sorting.
Every request scored on who's asking and what's at stake: paying customers and money-touching issues get more care and a human, routine questions move fast. Priorities and escalations decided the way your best rep would.
You don't have to switch it all on at once. We start on your safest, highest-volume queue and expand from there. See how →
No one hands a bot the whole queue on day one. We ship the way the airline system did: prove it on the safe lane, then widen it as it earns trust.
Where the volume and the waiting actually pile up — and which requests are safe to automate and which are not.
The agent runs alongside your team on the lowest-risk queue first, drafting with a person approving, until the drafts earn confidence.
More channels, more autonomy on the routine — always with a person on the sensitive, and monitoring so quality shows up on a dashboard, not in a complaint.
No. It takes the volume and the waiting off your team — the repeat questions, the drafting, the routing — and escalates anything hard or sensitive to a person. A human still owns anything touching money or an account change.
Guardrails tied to risk. Anything touching money, cancellations or account changes is held for a human before it goes out, and repeat or paying customers can be treated with more caution. The agent answers on its own only where being wrong is cheap and easily reversed.
Yes. It drafts email and chat replies, powers a knowledge-base chatbot for self-serve, summarises calls with action items, and reads incoming documents to route them to the right ticket or case. It works from your own knowledge base and connects to your CRM for context.
It starts narrow — on one low-risk queue, running alongside your team with a human approving drafts — so you see it working on a small, safe slice before it scales. It then expands to more queues and more autonomy as it earns trust, exactly how it rolled out for the airline.
Reef TRH