AI for businesses in Mallorca: choosing your first process

A company’s first artificial intelligence project should have a specific task and an outcome that can be checked. “Put AI in the business” is too broad to decide what to build, how much to invest or whether it worked.

At SOM-OS in Inca, we suggest starting with a process the team already knows. First, we understand how work happens today; then we assess whether it needs conventional automation, an AI agent or better information.

Choose a repeated task, not an entire department

Preparing information before a sales call, classifying requests or finding answers in internal documentation are candidates that can be given a clear scope. The choice depends on your data, the frequency of the task and the cost of getting it wrong.

These are design examples, not guaranteed results:

Process	Possible first delivery	What to measure
Sales enquiries	Summary and classification for review	Preparation time and classification errors
Support	Drafts based on documentation	Corrected responses and review time
Internal documentation	Search with source references	Useful answers and queries without information
Administration	Data extraction with validation	Corrections and time per document

Review the sources before choosing the model

Where is the information? Who maintains it? Which data is reliable, and which is out of date? An agent connected to incomplete documentation can produce a convincing answer that is no help in making a decision.

If each tool holds a different part of the process, an integration may be needed first. Our page on artificial intelligence for businesses in Mallorca explains how we connect sources, context and actions.

Define what it can do and when it must stop

Looking up information, writing a draft and executing an action have different consequences. Decide which permissions each task needs and which tasks require human approval.

To begin with, it is often useful for the agent to prepare a proposal for a person to review. If its autonomy is expanded, there must be logs, limits and a way to detect failures. Citing sources helps people review an answer; it does not, on its own, eliminate model errors.

Test with examples from the real process

Prepare typical requests, incomplete cases and situations in which the system should say it does not have enough information. Decide in advance what counts as correct and who will review the results.

Compare time and quality with the previous way of working. Include the time spent correcting answers. If a task is better solved with a rule or a straightforward integration, it does not need a language model.

Expand after checking the first delivery

The Sando Capital case study shows an investor acquisition and qualification workflow connected to appointments. The Nemus Arboricultura project shows the importance of organising processes and data in an application first.

If your business needs that foundation, explore our application development service in Mallorca. If you do not yet know where to start, the Chaos Map helps organise processes, tools and priorities before building.