AI answers the routine questions. People take the hard ones.

An AI agent takes over the questions that come back every day and have a clear answer in your documentation: order status, delivery times and options, return or warranty terms. It answers from your terms, descriptions and internal guidelines, and when they hold no answer, it hands the case to a person instead of guessing. The clearer and more current your documentation, the more questions the agent can handle on its own.

That is why we start with an analysis of incoming requests. We group them by topic and pick the most frequent ones for the agent to start with. The first version then covers the questions that weigh most on your team, and new topics are added step by step once we see how it works. The agent is part of our AI business process automation service, but here the goal is a single one: customers who write or call get an answer without waiting for a free person.

A conversation reaches a person when the case is complex, sensitive or needs judgement. Examples are a complaint, a payment dispute or a question your documentation does not answer. We agree the handover rules with you in the first week and build them into the first version of the agent. They can depend on the topic, the channel or the type of customer. Customers can also ask for a person themselves: the handover is part of how we build the agent, not an exception.

The goal is not for AI to replace your team. The agent takes the repeats, and people deal with the cases that need judgement. Your colleague receives the case with a short summary of the conversation, so the customer does not explain everything from the start. At peak times this is the difference between a queue of simple questions and a team that has time for the difficult ones.

In chat and by email the AI agent answers in text, using the same documentation and the same handover rules. A customer then gets the same answer whether they write in chat or send an email. On the phone an ElevenLabs voice agent answers the call, logs the request and transfers to a person when needed. If your main problem is calls outside working hours, see the page on voice agents for missed calls.

The agents connect to the systems you already use, such as a CRM or a ticketing system, depending on their integration options. An answer can then include details of the specific order, and a handed-over case lands where your team already works. You do not need to change your system. The agents are also set up for the languages your customers write and speak in.

The effect is measured against a baseline agreed before launch. In the first week we choose the metrics together, such as response time, the share of requests the agent handles on its own and the load on your team. The pilot runs on real requests under supervision, and the first measurable results usually come within 2–4 weeks of the start. The pilot results also show which topics to add next. If the agent does not deliver, it does not reach production. We stop it and pick the next process.

The agents can be a standalone project or part of a full AI transformation with the Encorp AIM (AI Implementation Method). There customer support is one of the processes chosen at Gate 1, with the first quick win by week 4 and solutions in production in weeks 11–12. After go-live the agents move to AI Ops: support, new topics and improvements every month, with response within 24 hours.