Chatbots answer, but they don't resolve
A traditional chatbot can tell you "your order is being prepared", but it can't change it, cancel it or reschedule the delivery. That always takes a person.
The problem
Passive assistants fall short
Giving good answers is no longer enough. The real difference is AI that also takes action.
Repetitive tasks that mean jumping between systems
Adding a customer to the CRM, creating their contact in the billing system, sending the welcome email and scheduling the sales call. 6 systems, 12 minutes, a thousand times a month.
Scattered data that nobody connects
The right answer to a customer's question is spread across 3 different systems. Nobody has time to check all 3 at once, so customers get half an answer.
Manual processes that can't handle more volume
As the business grows, the team can't scale at the same pace. You need an assistant that takes care of the mechanical tasks so your people can focus on work that adds value.
Comparison
It's not a chatbot. It's not a macro either.
Where an AI agent fits compared with the two alternatives you probably already know.
| Capability | Chatbot | RPA / macro | AI agent |
|---|---|---|---|
| Understands natural language | Yes | No | Yes |
| Decides the steps on its own | No | Fixed script | Yes |
| Takes action in your CRM, ERP and email | No | Yes | Yes |
| Adapts when the case changes | No | Breaks | Yes |
| Chains multiple tasks and systems | Limited | Rigid | Yes |
| Scales to new cases | No | Needs reprogramming | With tuning |
| Logs and explains what it does | Partly | Logs | With reasoning |
The chatbot talks. RPA repeats. The agent understands, decides and executes.
How it works
The 4 stages of an autonomous agent
A well-designed agent understands, plans, executes and reports — without you having to watch over it.
Understands
The agent reads the user's request or the triggering event (incoming email, form, message) and works out what is being asked.
Plans
It decides which steps to take and in what order. If the task is complex, it breaks it down into smaller subtasks.
Executes
It queries your systems (CRM, ERP, calendar, email), calls the connections it needs and completes each step of the task.
Reports
It lets you know when it's done, with a summary of what it did. If something couldn't be closed, it escalates to a person with the full context.
Live trace
How a real agent reasons and acts
A simplified example of how the agent breaks down a request and closes it out step by step.
USER Cancel order 3142 from Logistas SA and send the customer an apology.
→ THINK Task identified: cancel order + notify customer. Steps required: 3.
🔧 TOOL ERP.cancel_order(id=3142) → ✓ Cancelled.
🔧 TOOL CRM.find_contact(company="Logistas SA") → email: orders@logistas.es
🔧 TOOL Email.send(recipient, template="cancellation_apology") → ✓ Sent at 14:32.
✓ DONE Task completed. Order 3142 cancelled and Logistas SA notified. No restocking cost, as it was still being prepared and hadn't shipped.
Use cases
Where an agent makes the difference
Six scenarios where the time savings and consistency show from the very first week.
Sales assistant
Qualifies leads, books meetings, prepares proposals and updates the CRM at the end of the day on behalf of your sales reps.
Technical support
Reads the customer's ticket, checks the system logs, suggests the fix and, if it's a standard answer, applies it directly.
Back office
Processes supplier invoices, matches payments in the bank, updates the accounts and flags exceptions.
Data analysis
Queries multiple sources, cross-references the data and produces the weekly report with your key business figures.
Operations and logistics
Schedules deliveries, flags delays and keeps order status in sync across every system — no phone calls, no spreadsheets.
HR and onboarding
Sets up new employees in every tool, prepares their access and schedules their first day. What used to take hours now takes minutes.
Security and control
You're in charge. The agent only does what you authorize
The question isn't whether AI can touch your systems, but within what limits. These are our defaults.
Scoped permissions
The agent only accesses what it strictly needs, with its own credentials that can be revoked at any time.
Human approval
Critical actions — paying, deleting, writing to a customer — wait for your go-ahead before they run.
Fully traceable
Every step is logged: what it checked, what it did and why. Auditable and reversible.
Rules it never breaks
Fixed business limits — maximum amounts, allowlists, time windows — that the agent never crosses.
Your data, under control
Self-hosted models or models covered by a no-training agreement. GDPR compliance by design.
Supervised start
It starts by making suggestions and, as your confidence grows, begins acting on its own. You set the pace.
Integrations
How the agent links your systems together
A single request can move data between your CRM, ERP, calendar and email — without anyone copying and pasting.
Request
An email, form or internal message comes in with a specific task.
CRM lookup
The agent retrieves the customer record, their history and relevant contacts.
ERP action
It creates, updates or closes the transaction in your management system (order, invoice, ticket).
Outgoing email
It sends the confirmation, summary or apology to the customer using the right template.
Closing report
It records what it did and alerts the team if anything needs human review.
How we work
From idea to an agent in production
A phased process: start small and expand as your confidence grows. No months-long megaprojects.
1
Assessment 1 week
Together we identify the task with the highest return and map the systems and data involved. We come out with a clear, measurable use case.
2
Agent design
We define what it will do, which tools it will use, its permissions and at which points it asks for human approval. No surprises.
3
Supervised pilot
We build a tightly scoped first version and test it with real cases: the agent proposes, you approve. We adjust based on what we learn.
4
Production
We connect it to your systems with monitoring and traceability from day one. It starts saving real work.
5
Continuous improvement
We add more use cases and fine-tune it with your real usage. The agent gains autonomy as you gain confidence.
The impact
What changes when you bring in an agent
Indicative figures observed in real projects with sales, customer service and back-office teams.
FAQ
Frequently asked questions about AI agents
How is an agent different from a chatbot?
A chatbot talks and answers. An agent also takes action: it queries your systems, updates data, sends emails and completes tasks. The chatbot talks; the agent works.
Is it safe to let AI touch my systems?
Yes, if it's designed sensibly. We set the agent up with limited permissions and human approval for critical actions. Every step is logged and can be reviewed.
How much does a custom AI agent cost?
The cost depends on the use case, the systems the agent needs to access and its permissions. We analyze the process and send you a proposal with scope, timeline and a fixed price.
Does it work with the software I already use?
Yes. We integrate via APIs or connectors with your CRM, ERP and tools (Dolibarr, Odoo, HubSpot, Google Workspace, Microsoft 365 and many more). If something has no API, we find the most reliable alternative.
Can I start with something small?
That's exactly what we recommend. We start with a tightly scoped use case that proves its value quickly and then extend it to more tasks and systems based on your real-world feedback.
Which AI models do you work with?
We use the best model for each case: OpenAI GPT, Anthropic Claude, Mistral or open-source models hosted on your own server when confidentiality requires it.
What if the agent makes a mistake?
We build the agent with a safety net: validations, human approval for anything critical and the ability to roll back actions. And it learns from the mistakes that get corrected.
How long until it's up and running?
An agent focused on a specific use case can be up and running in 4–6 weeks. We start with a useful first version and extend it based on your real-world feedback.
Does the agent learn and improve over time?
It improves with your corrections and new examples, and we fine-tune its instructions and tools based on real usage. It never retrains itself without your control: you decide when it earns more autonomy.
Your next step
Let's put your first agent to work
Tell us which repetitive task takes up most of your time and we'll design the agent that handles it for you. A no-obligation initial assessment and a fixed-price proposal in under a week.