ARTIFICIAL INTELLIGENCE FOR BUSINESSES

Turn company knowledge into work with AI

Access to AI tools does not automatically create a system that delivers results. SmartLinks organises knowledge, data and rules and builds the layer the problem needs, from research and answers to integrations and agents.

EXECUTION

AI delivers little when a company starts with the tool

Buying another copilot or opening another account does not solve scattered knowledge, outdated data or processes nobody can explain consistently.

Without a shared foundation, answers vary, teams repeat context, integrations fail and an agent can execute the wrong task faster.

Preparation starts before the model. We need to know what information should be used, where it lives, who validates it and which actions can run without human intervention.

Only then does it make sense to choose between simple question and answer, chat, automation, MCP integration or a group of agents.

Scattered knowledge and data

The company has information, but it is distributed across documents, CRM, applications and people. AI cannot use it consistently.

Automation without context or control

A tool can execute tasks. Without rules, limits and validation, it can also multiply errors and create more work.

AI ARCHITECTURE

One shared foundation. Different AI layers.

Not every company needs the same technology. Every company needs organised information, accessible data and clear rules. From there, we build only what the use case requires.

01

Centralising knowledge

Bringing together the offer, processes, criteria, examples, FAQs and decisions scattered across the company.

02

Connecting current data

Identifyig data that changes day to day: CRM, catalogues, requests, tickets or metrics. Defining how it can be queried.

03

Defining rules and boundaries

Turning the way your team works into clear instructions. The system knows what it can do, when it needs approval, and when to hand the case over to a person.

04

Choosing the right layer

The solution can be search and answer, chat, AI automation, an MCP connection or multiple agents. The level of complexity depends on the desired outcome.

05

Integrating with existing systems

Connecting AI to the tools it needs to access information or carry out tasks, while maintaining control, traceability and accountability.

06

Measuring and improving

Defining what good results look like, monitoring errors and exceptions, and improving the system based on real-world use.

Choose the application by the result you want to improve

AI Ready Transformation prepares the foundation. Agents apply that foundation to work. In sales they can research, qualify and prepare commercial actions. In customer support they can answer, route and execute simple tasks. In operations they can process information, update systems and manage exceptions.

OUR FIRST SYSTEM WAS OUR OWN

How we organised AI inside SmartLinks

At SmartLinks, knowledge was spread across documents, CRM, content, applications and people. Every new AI use case required us to explain again who we were, how we worked and what a good answer looked like.

We centralised what we want to do, examples of good and bad work, decisions and references in GitHub. Smartbot turns that foundation into rules for how we assess and execute work.

On top, we use the AI layer that fits each case. The result is not one tool, but a shared foundation for content, sales, reporting, automation and agents.

GitHub: centralised knowledge

Offers, decisions, criteria, examples and references are organised and versioned.

Smartbot: working rules

How we think, assess and execute no longer depends only on the memory of a few people.

AI Layer de IA: practical application

Each case uses the technology it needs, from a simple answer to integrations or agents, always on the same foundation.

FREQUENTLY ASKED QUESTIONS

Frequently asked questions about artificial intelligence for companies

Does my company need AI agents?

Only if there is a concrete task that requires interpretation or execution. If a simple rule solves it better, we use automation. If the problem is scattered information, we start with the foundation.

Is an AI agent the same as a chatbot?

No. A chat is an interface. An agent can query data, choose the next step, use tools and execute actions within defined limits.

Do we have to use HubSpot?

No. HubSpot can be a data source and an execution environment. The architecture depends on the systems the company already uses and the problem it wants to solve.

Where does a AI project starts?

It starts with the problem. We map the task, information, rules, risks and how to measure the result. Only then do we define the technology.

Not every process needs AI. The first step is to understand where it can make an impact and where it makes sense to implement it.

BOOK A MEETING

Where could AI remove work or improve a decision in your company?

Book 30 minutes with Rui Martins, CEO and co-founder of SmartLinks. We will discuss the problem, available data and the result that would make a difference. By the end, it will be clear whether there is a case worth diagnosing.

30 minutes · Free · No commitment