AI & automation
Website copy, social posts and emails in your brand voice: fast and at scale.
AI generates drafts and variations from your prompt and brand voice; you review and approve. Product descriptions, posts, emails and localisation into 3 languages without scaling up the editorial team.
AI content generation means creating website copy, product descriptions, social posts, email campaigns and translations using LLM models (GPT and equivalents) tuned to your brand voice and style. AI produces drafts and variations in seconds; an editor reviews and approves. It lets you generate hundreds of content pieces in hours without a large team and keep a consistent brand voice across 3 languages (RU, ES, EN). Gartner predicted back in 2022 that by 2025, 30% of large-company marketing messages would be synthetically generated. Request a quote and we reply within 24-48 hours.
Here we explain AI content generation for businesses across Spain: which formats it covers, how brand voice is configured, how localisation into Russian, Spanish and English works, and how to build a process where AI handles drafts and humans handle quality control. By AI content generation we do not mean one-off ChatGPT prompts, but a structured pipeline: prompt engineering, brand knowledge base, SEO instructions and human review before publishing. Below you will find a step-by-step launch plan, a table of applications by content type, Gartner data on the growth of generative AI in marketing, and answers to common questions. At the end, our "AI & automation" packages and related services.
The common mistake is running AI without a defined brand voice or prompt system, getting generic text and feeling disappointed. The right path is different: document your brand voice, write a system prompt, tune the LLM on your sample texts and launch one pilot format, for example product descriptions or social posts. In 1-2 weeks you have a ready pipeline, then scale to other formats and languages.
AI generation covers most business text formats: product and category descriptions for online stores, posts and captions for social media, landing page and website section copy, email sequences and newsletters, plus localisation of all of the above into multiple languages. The pipeline is built once and formats are added as needed. Below is a reference of applications and recommended LLM models.
| Format | AI application | Localisation | Human role |
|---|---|---|---|
| Product descriptions | Bulk generation from template and product attributes | RU / ES / EN in one pass | Check tone and spec accuracy |
| Posts and captions | Platform-specific variants (Instagram, LinkedIn, X) | Cultural context adaptation | Pick best variant and edit hashtags |
| Email sequences | Nurture, promo and reactivation sequences by segment | Translation preserving CTA and tone | Final edit and subject line A/B test |
| Website copy | Landing pages, service pages, section SEO copy | Localisation with hreflang and keywords | Brand and SEO compliance review |
Generative AI already handles the routine part of content production: first drafts, headline variants, adaptation to formats and languages. It does not replace the editor; it amplifies them. The human defines the task, sets the brand voice, picks the best option and does the final edit. The scale of the shift is visible in the numbers: Gartner predicted back in 2022 that the share of synthetically generated marketing messages from large companies would rise from around 2% in 2022 to 30% by 2025. For small and medium businesses in Valencia and across Spain, the "AI + editor" hybrid model means content production at the level of large brands without a bloated team. Below is Gartner's forecast on the scale of this shift in marketing.
«Gartner predicted back in 2022 that by 2025, 30% of outbound marketing messages from large organizations would be synthetically generated — up from around 2% in 2022. This forecast reflects how quickly the hybrid "AI + editor" model is changing the speed and cost of content production.»
AI content generation lets you produce website copy, product descriptions, posts and emails at scale without a large editorial team. The key is to set up your brand voice and prompt system once, then replicate it across all formats and languages. LLM models (GPT and equivalents) generate drafts; the editor reviews and approves the final. Localisation into RU, ES and EN is built into the same pipeline. Large companies are already actively adopting the "AI + editor" hybrid model for marketing content production. Start with one pilot format (product descriptions or posts) and scale from there. Request a quote and we will prepare your plan and estimate for "AI & automation" within 24-48 hours.
AI and automation
n8n, Make, GPT-API, voicebots and document OCR, from €490, paid once. We count the hours routine work eats up and automate exactly that: basic automation is live in 4-5 days.
We start by mapping your processes: we find where someone copies data by hand from an email into a spreadsheet and from there into the CRM, and remove exactly those steps. It goes in once and the automations then run on their own, with no monthly fee to us. Everything is built on your accounts and credentials, so the solution stays yours even without us. Custom AI development in Spain starts at €3,000; our Start tier is six times cheaper.
A short brief, and we’ll come back with a plan and quote within 24-48 h. No pressure.
It is the creation of texts (product descriptions, posts, emails, landing pages) using LLM models (GPT and equivalents) tuned to the brand voice and SEO requirements. AI generates drafts; the editor reviews and approves the final. That way dozens of texts in one format come out in hours instead of weeks, and in a consistent style.
Yes, with the right setup. The LLM receives a system prompt with brand voice description, text samples and banned phrases. The more precise the prompt and the more samples, the more consistent the output. Before launch we run several test texts and compare them with your best samples.
Yes. AI delivers drafts and variants fast, but fact-checking, brand compliance and final editing remain with the human. This is the "AI + editor" model: speed from AI, quality from the human. The editor gets to review and correct rather than write from scratch, which is many times faster.
Modern LLMs handle Russian, Spanish and English confidently, the studio's three working languages. Localisation is built into the same prompt pipeline: one request produces three versions with cultural context and SEO. Each version is checked by an editor who knows the language, not just the prompt.
At scale you get hundreds of content pieces in hours: product descriptions for a catalogue, a week of social posts, an email sequence. The bottleneck is not generation speed but the editor's review capacity. So the pipeline is built so the editor sees only what actually needs correction.
The prompt includes target keywords, structure requirements (H1, H2, meta description) and density instructions. The LLM weaves them in naturally without hurting readability. The final SEO check is done by a specialist. Keywords and structure come from the research done for your pages, not from generic lists.
Yes, this is one of the most common use cases. You provide product attributes and a template, and AI generates a unique description for each item. For catalogues with hundreds or thousands of SKUs this fundamentally changes content speed and cost.
Regular translation converts words; localisation adapts meaning to the culture and context of the target market. With the right prompt, AI accounts for idioms, forms of address and target-language SEO keywords simultaneously. Every version is still proofread by an editor who knows the market's language. Tone of address, units and local terms are checked separately.
We run the project in Russian, Spanish and English, the studio's three working languages. We deliver documentation, prompts and instructions in your preferred language. Support and quality control too. Prompts are written in the same language the content will be published in; the results are more stable that way.
Audit of existing content and brand voice, system prompt development, pipeline setup for your formats, testing on real data, editor instructions and launch support. LLM platform access is paid separately at their own rates. We state the subscription costs before the start so the full budget is visible.
