Reunião de 30 minutos com o Rui Martins. Sem custos, sem compromisso e sem necessidade de preparar nada.
Before
AI AGENTS FOR SALES
A sales team does more than sell. It researches accounts, organises notes, prepares meetings, updates the CRM and works out the next step. We build AI agents that take on part of that work using your company’s data and rules.
WHERE TIME IS LOST
Opportunities are rarely lost because a team lacks a tool. They are lost when context stays in personal notes, follow-up arrives late, or no one knows which account deserves attention first.
Sales teams also spend hours researching companies, summarising conversations, filling in CRM properties and preparing messages that start from scratch every time.
Traditional automation handles predictable tasks. An AI agent steps in when information must be interpreted, signals compared and the next action adapted to the context.
The goal is not to put a machine in charge of selling. It is to remove preparation and admin so the team can spend more time in the conversations where people make the difference.
Account, contacts, activity, notes and relevant signals are summarised so the salesperson arrives prepared.
The system identifies tasks, prepares follow-up and keeps the CRM updated within the rules you define.
WHAT AN AI AGENT CAN DO
An agent is designed for a specific job. It can support one stage or several, as long as the data, rules and controls are strong enough.
Brings together public information, CRM history and internal signals to create a useful briefing before outreach or a meeting.
Compares available information with the ICP and sales criteria, flags risks and explains why it recommends moving forward, reviewing or disqualifying.
Summarises the relationship, identifies open topics, retrieves previous proposals or interactions and suggests relevant questions.
Extracts decisions, objections, commitments and dates from conversations and prepares record updates for validation.
Creates a first draft based on what was discussed, the agreed next steps and the company tone.
Crosses activity, time without a response, deal stage and defined criteria to show what needs action.
The agent needs a knowledge base with the offer, ICP, examples and criteria; current CRM and interaction data; and rules defining what it can prepare, update or execute. The AI model is the layer on top. Without this foundation, it only produces text faster.
THE FIRST CASE WAS INTERNAL
At SmartLinks, qualification criteria already existed. The problem was that they were spread across documents, team experience and CRM information.
We centralised the ICP, risk signals, decision criteria and examples. The system can compare these elements with an incoming enquiry, suggest a classification and record the reasons.
The commercial decision remains human. The agent reduces research work and makes the reasoning visible so it can be reviewed.
Before
With the agent
Human control
FREQUENTLY ASKED QUESTIONS
No. It takes on research, preparation and admin tasks. Relationships, negotiation, judgement and decisions remain with people.
It can, when the use case and risk allow it. Many companies start with human approval and only automate actions after validating quality, rules and exceptions.
It is not required. The agent needs an organised source of commercial data. HubSpot is a strong option, but we assess the infrastructure you already have.
Automation executes a predictable rule. An agent interprets context and adapts the next step. We use automation when the rule is clear and AI when variability or judgement is involved.
We do not start by choosing the agent. We start by identifying which sales work is consuming time without improving the customer relationship.
Book 30 minutes with Rui Martins. We review your sales process, CRM and the tasks that consume time. You leave knowing whether there is a use case worth diagnosing.
30 minutes · Free · No commitment
Reunião de 30 minutos com o Rui Martins. Sem custos, sem compromisso e sem necessidade de preparar nada.