AI AGENTS FOR CUSTOMER SUPPORT

AI agents for customer support that resolve more without losing context

Support teams answer the same questions, search across systems and hand over requests without the right context. We build AI agents that handle routine requests, support the team and route exceptions to the right person.

WHERE SUPPORT GETS STUCK

Your team spends time rebuilding the context of every request

Customers explain the issue by email, repeat it in chat and describe it again when the case changes hands. Your team searches documents, tickets, CRM records and colleagues’ memory for the answer.

A generic chatbot can recognise words and return a reply. That is not enough when the system must understand the customer, check current data, apply a rule or decide that a person needs to step in.

An AI agent combines knowledge, data and rules. It resolves what is safe to resolve, prepares what needs approval and hands exceptions to the team with the history they need.

The goal is not to keep people away from customers. It is to remove repetitive questions and triage so the team can focus on cases where judgement and relationships matter.

CONTEXT

The answer starts with what the company already knows

Policies, procedures, history and account data should not be separated from the conversation.

ESCALATION

The right person receives the complete case

When the agent should not proceed, it routes the request with a summary, priority and the information already collected.

WHAT AN AI AGENT CAN DO

AI agents for customer support, designed around real work

Each agent is designed for a specific request and a defined level of autonomy. We start with frequent tasks, clear rules and outcomes that are easy to check.

01

Answer frequently asked questions

Uses approved knowledge to prepare a consistent answer aligned with the company’s procedures, products and language.

02

Identify and classify the request

Interprets intent, collects missing information and assigns topic, priority or responsible team according to defined criteria.

03

Consult customer data

When integrated, cross the conversation with account, order, contract or ticket data to avoid generic answers.

04

Execute simple actions

Can schedule, update, create or look up a record when the task is authorised and its limits are defined.

05

Hand the case to a person

Recognises exceptions, risk or low confidence and transfers the request with a summary, relevant data and steps already taken.

06

Show where the service can improve

Tracks recurring themes, failed answers and unresolved requests to improve knowledge, processes and the product.

An agent needs to know, consult and recognise its own limits

The foundation combines validated knowledge, current system data and decision rules. We define when the agent can answer, which actions it can execute and when it must hand the case to a person. Autonomy increases only when real work demonstrates sufficient quality.

THE FOUNDATION IS BUILT INTERNALLY

How we organise the knowledge that powers SmartLinks AI agents

At SmartLinks, information about services, processes, criteria and decisions was spread across documents, applications and people. That meant rebuilding context whenever a new question appeared.

We centralised knowledge and examples, turned the way we work into rules and created a base that different AI layers can consult.

The same principle applies to customer support. First organise what the company knows and define who validates it. Then connect the agent to the data and actions each case requires.

Centralised knowledge

Offers, procedures, criteria and examples are available in a shared knowledge base.

Explicit rules

The system distinguishes an approved answer, an authorised action and a case that requires a person.

Controlled execution

The AI layer responds or executes only within the defined context and limits.

FREQUENTLY ASKED QUESTIONS

Frequently asked questions about AI agents for customer support

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What is the difference between an AI agent and a chatbot?

Chat is a conversation channel. An agent can consult systems, interpret context, choose the next step and take actions within defined rules.

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How do you prevent incorrect answers?

We limit knowledge sources, define confidence rules, log responses and route to a person when data is missing or risk is present.

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Can it work across email, chat or WhatsApp?

It can work in channels that support integration and where the right data and processes exist. We choose the channel after identifying the request and the action to improve.

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Does the agent replace the support team?

That is not the goal. The agent handles repetitive work, prepares answers and triages requests. The team keeps sensitive cases, exceptions and conversations that require human judgement.

If the company’s knowledge is not organised, we start with that foundation before automating the customer conversation.

BOOK A MEETING

Which requests are consuming time before a person needs to step in?

Book 30 minutes with Rui Martins. We review your most frequent requests, information sources and the moments when your team should take over. You leave knowing whether there is a use case worth diagnosing.

30 MINUTES · FREE · NO COMMITMENT