An AI marketing agency that puts AI to work inside your team

Many teams already use AI assistants daily, each person in their own way, with personal accounts and no common standard for data or review. The goal is to move from individual experiments to a shared way of working that is documented and measurable.

This page covers strategy, governance and training. For the build, AI agents handle customer enquiries and marketing automation connects your CRM, email and campaigns. We work from Palma de Mallorca for businesses across Spain and abroad.

AI delivers most on frequent tasks with clear quality standards that a person can check quickly. So we list what your team does each week and rank it by impact, risk and effort before choosing any tool. The order changes by sector: in hotels and tourism, reviews and enquiries in several languages tend to come first; for a consumer brand with an online shop, product pages and ad variants.

• Research: competitors, reviews, search behaviour and briefings.
• Content: outlines and drafts a person edits before publication, just as in our content marketing.
• Ad creative: copy and image variants for search and paid social, within your brand rules.
• Reporting: summaries, anomaly spotting and first-pass analysis of your analytics data.
• Qualification: sorting inbound enquiries for your sales team.

AI governance means deciding in writing which tools are used, with which data, who reviews each output and how customers are informed. Together we draft a short AI usage policy, a tool inventory and a data classification: what may go into an assistant, what only into business-grade tools and what never. In a private clinic, for example, the policy starts by keeping patients' health data out of any general-purpose assistant. Each policy names an owner and is reviewed when the tools or the rules change.

GDPR information duties apply when customer data passes through AI tools, and we only say data isn't used for model training when the settings and contract guarantee it. Human review is not a formality either: Google's spam policies treat mass-produced content without value as abuse, AI included.

AI adoption works better through small, measured pilots than a company-wide rollout: we pick two or three workflows, measure them, redesign them with AI, compare and scale only what proves its worth.

Tool selection comes after the use cases, not before, and compares every option on the same four criteria. Sometimes the business licence of an assistant you already pay for is enough; sometimes you need a custom AI agent. Unsure which channels to prioritise? Start with digital strategy.

• Data: where it is processed, how long it is kept and whether the vendor uses it to train its models.
• Contract: a business licence, a data processing agreement and admin controls.
• Integration: whether it fits your CRM, CMS and analytics without manual work.
• Adoption: whether your team will really use it, and what training that takes.