AI agency in Brussels · AI agents, chatbots & automation
AI, only when
it does it better.
Clyde & Bonnie designs and integrates AI agents, customer support chatbots and multi-agent systems built around your processes, your teams and your tools.
AI agency · Advice, build & integration
AI is a tool. Not an end in itself.
Adding a chatbot or plugging in a model does not transform a company. The tool only becomes useful once it understands the right context, reaches the right information and steps in at a precise point of the process.
Before talking about models, agents or automation, we look at what is actually happening on your side: the repetitive tasks, the delays, the errors, the customer requests, the existing tools and the decisions that tie your teams up for nothing.
The solution comes after. Sometimes it is a support chatbot. Sometimes an AI agent connected to your tools. Sometimes several specialized agents handing over to each other. And sometimes AI is simply not the best answer.
What our AI agency does
From the business need to an agent that actually works.
We can step in on one specific stage or take on the whole project: needs analysis, architecture, development, integration, testing, deployment and continuous improvement.
We map the processes, the volumes, the friction, the data available and the tools already in place. The goal is not to find a use for AI at any cost. It is to identify the tasks where it can genuinely cut a delay, improve an answer or free up time.
We build custom AI agents able to look up information, analyze a request, produce an answer, use tools or trigger an action inside a defined frame. Every agent gets a role, data, permissions and clear limits.
Built into your site, the bot answers questions, qualifies visitors, scores and routes leads or hands over to a human. It draws on your content, speaks in your brand’s voice and follows your rules. Not a standard demo’s.
Procedures, documents, offers, contracts, catalogues or domain knowledge: an internal AI assistant helps teams find an answer and act on it without digging through several tools. Access stays matched to roles and to what each person may consult.
Qualifying a request, triaging tickets, preparing a file, summarizing, checking or updating a tool: we bring AI into the steps where it can assist or execute. With human sign-off whenever the stakes or the risk call for it.
When a process is too complex for a single agent, we design a multi-agent system. One agent analyzes, another searches, a third executes or verifies. An orchestration layer coordinates the roles, the handovers and the checks.
An isolated agent is just a better chatbot. We connect it to the sources and tools it needs: website, CRM, helpdesk, document base, catalogue, APIs or internal applications. It only reaches what it needs to do its job.
We track the answers, the failures, the escalations, the costs and the usage. Instructions, sources, tools and guardrails evolve from what actually happens. So that your agent stays genuinely useful.
Custom AI bot · Support, qualification & conversion
A form is fine.
A bot is better.
Your competitors have a contact form. You can have an AI bot that answers, qualifies and directs your visitors around the clock, then hands over to a human when the request calls for it.
Built to measure, it takes on your brand’s voice, draws on your services and your content, answers questions, asks the ones that are missing and moves every visitor closer to the right next step. The journey follows your rules. Not a standard chatbot’s.
We build the bot on whichever model fits the project: OpenAI, Anthropic, Mistral or another. It is integrated straight into your site, with no platform lock-in and no intermediary imposed between you and your data.
Custom AI chatbot
The right model for your case, your brand’s voice, your content and your rules. The bot is configured, tested and deployed straight onto your site, with a handover to a human when the situation calls for it.
Conversation logging
Every conversation is logged according to the rules we set with you. Exchanges stay readable and analyzable, so answers can be improved, the knowledge base enriched or the model refined where that is justified.
Lead qualification flow
The bot asks the right questions, qualifies and scores the requests, then routes every lead to the right person or the right tool. Fewer forms without context. More conversations ready to be handled.
Multi-agent architecture & orchestration
Specialized agents. Clear orchestration.
Some processes need several skills, several tools or several levels of control. Handing all of it to a single agent makes the system hard to steer and harder still to verify.
A multi-agent architecture splits the work between specialized agents. One interprets the request, another looks up the information, another performs an action and a last one checks the result. The orchestrator decides which agent steps in, in what order and under what conditions.
We do not multiply agents to make the diagram look impressive. A multi-agent system only makes sense if it makes the process clearer, more reliable or easier to evolve. When one agent is enough, one agent is enough.
A full training system for clinical interviewing.
For Sialab, we designed a multi-agent architecture for training clinical interviewing in psychology. One agent plays a voice-based AI patient, others analyze the session, and Sia turns the results into personalized supervision. Every agent has its role. The experience stays seamless.
Discover Sialab →Data, security & human oversight
Automating does not mean letting go of the controls.
We define the allowed sources, the access rights, the possible actions, the escalation cases and the human sign-offs. The more data an agent reaches or actions it performs, the tighter its frame has to be.
We test the expected answers, the ambiguous situations and the cases where the agent has to stop rather than improvise. An AI agent can produce an answer that is plausible and still wrong.
Security, privacy and compliance requirements are built into the project as the context demands. We work with your technical teams, your DPO or your counsel when sign-off goes beyond the scope of the implementation.
An AI agency that also understands the customer journey
A good agent will not save a bad process.
A chatbot can answer correctly and still fail because the source information is confused. A qualification agent can work fast and pass on bad leads. An automation can save time on one step and waste it on the next.
Clyde & Bonnie combines AI with marketing strategy, web, copy, acquisition and tracking. So we can look at what happens before the agent steps in, what it has to achieve and what comes after.
We do not leave you with a list of tools or an isolated prototype. We can design the architecture, build the agents, integrate them into your processes and improve the touchpoints that have to work with them.
FAQ · AI agency, AI agents & chatbots
Simple questions.
Honest answers.
What does an AI agency do?
An AI agency helps companies identify, design and integrate artificial intelligence into their operations. It can work on strategy, AI agents, chatbots, automation, knowledge bases, integrations and multi-agent systems.
A good AI agency does not start by selling a tool. It starts from the process, the data, the users and the expected outcome to work out whether AI is genuinely relevant.
What is an AI agent?
An AI agent is a system built to carry out a task inside a defined frame. It can understand a request, look up information, reason about the steps to take, use tools and sometimes trigger an action.
How autonomous it is depends on the permissions, the integrations and the controls in place. Not every AI agent should act alone. Some tasks call for human sign-off.
What is the difference between a chatbot and an AI agent?
A chatbot is mainly built to converse with a user. It answers questions, guides a conversation or collects information. An AI agent can go further: consult several sources, use tools, update a system or run a series of steps.
So a customer support chatbot can be an AI agent, once it stops merely answering and starts genuinely handling the request.
What is a multi-agent system?
A multi-agent system brings together several specialized AI agents working on the same process. Each agent gets a defined role, and an orchestration layer organizes when they step in, what they exchange and how they are validated.
That architecture helps when a task needs several skills or several checks. It is not automatically better than a single agent, and it adds complexity that has to be justified.
Can you build a support chatbot from our own content?
Yes. A support chatbot can be connected to an FAQ, a document base, product sheets, procedures and other internal sources. We organize the content, the access rights and the answering rules so the agent relies on the right information.
It can also qualify a request, prepare a ticket or hand the conversation to a human with the context already gathered.
Can you connect an AI agent to our existing tools?
Yes, when those tools expose the access and integrations needed. An agent can be linked to a CRM, a helpdesk, a website, a document base, a catalogue, APIs or internal applications.
We define precisely what data it can read and what actions it can perform. An integration is only opened when it serves the process and can be controlled.
Which AI models do you work with?
We do not choose a model before understanding the need. Depending on the use case, the data, the integrations, the speed, the cost and the hosting requirements, we can work with models from OpenAI (GPT), Anthropic (Claude), Google (Gemini), Mistral or open source.
The choice comes after the framing. Not before.
How do you choose which processes to automate with AI?
We look for tasks that are repetitive, high-volume, slow or hard to handle with the current tools. Then we weigh the quality of the data, how often exceptions occur, the risk of error, the need for human judgement and the expected value.
The best first projects are usually useful enough to produce a visible effect and contained enough to be tested properly.
How do you limit errors and hallucinations?
We reduce the risk by framing the sources, the instructions, the tools, the permissions and the escalation cases. We also test ambiguous questions, out-of-scope requests and the situations where the agent has to refuse or ask for validation.
No generative AI system is infallible. The level of autonomy has to stay proportional to the consequence of a mistake.
How much does building an AI agent cost?
The budget depends on the process, the number of integrations, the quality of the data, the level of autonomy, the interfaces, the testing and the security requirements. A chatbot connected to a knowledge base and a multi-agent architecture acting across several tools are not the same project.
We quote after framing the need. That avoids the seductive prototype that forgets integration, supervision and the work it takes to reach production.
How long does it take to build an AI agent?
It depends on the scope, the data, the integrations and the level of risk. A focused first version can be tested quickly. A system connected to several tools, or able to perform actions, needs more design, testing and validation.
We move in stages with checkpoints. The first goal is to verify usefulness and reliability before extending autonomy or the number of users.
Do we have to replace our current tools to bring in AI?
Not necessarily. In many cases the AI agent connects to the tools already in use and steps into one precise part of the process. Replacing a CRM, a helpdesk or a document base only to add AI can create more work than value.
We favour integration when the existing base is sound. Changing tools is only recommended when the current limits genuinely block the project.
Do you work with companies in Brussels and Belgium?
Yes. Clyde & Bonnie is an AI agency based in Brussels. We work with SMEs, scale-ups, institutions, organizations and larger companies in Belgium and abroad.
Workshops, testing and follow-up can happen with your teams in Brussels or remotely.
See whether AI is the right answer.
Got an idea for an AI agent, a support problem or a process eating too much time? Explain it to Marvin. He will help you pin the need down and see whether AI really deserves a seat at the table.