I've been conducting a systematic evaluation of several AI content generation platforms for a multilingual marketing project, with a specific focus on technical and long-form content. My workflow involves generating initial drafts in English, then producing localized versions in Spanish, German, and Japanese. I'm using a controlled set of source prompts and evaluating outputs across several dimensions: factual consistency, terminological precision, grammatical accuracy, and stylistic appropriateness for the target locale.
The performance of Copy.ai for the Spanish locale has been notably subpar, to the point of being unusable for professional purposes. The grammatical errors are not mere stylistic quirks; they are fundamental syntactical and morphological failures that suggest either a severely undersized Spanish language model, inadequate fine-tuning, or problematic pipeline processing. The issues are consistent and reproducible.
Primary symptom categories observed:
* **Incorrect article-noun gender agreement:** "el problema grave" might become "la problema grave."
* **Erroneous verb conjugations,** particularly in compound tenses and the subjunctive mood. Outputs frequently mix tenses within a single sentence.
* **Preposition misuse,** especially with "a," "de," and "en," which corrupts the meaning of technical phrases.
* **A pronounced "calque" effect,** where English syntactic structures are translated literally, resulting in Spanish that reads like a poor direct translation.
My technical hypothesis is that the Spanish model is either:
1. A disproportionately small model compared to the English counterpart, lacking the parameters for grammatical nuance.
2. Suffering from catastrophic interference during multi-task training, where optimizing for English degrades performance in other languages.
3. Using a flawed tokenization or detokenization process for Romance languages.
Before I abandon the platform for this use case, I wanted to query the community. Has anyone successfully developed a workflow or series of prompts that forces Copy.ai to produce grammatically correct Spanish? I have attempted several mitigation strategies with limited success:
* **Preemptive prompting:** Adding "Escribe en un español gramaticalmente perfecto, adecuado para un público técnico en España." to all instructions.
* **Template constraints:** Providing a strict JSON output format hoping to constrain sentence structure.
* **Two-step generation:** First generating a list of key technical terms, then requesting a draft using those terms.
None have yielded consistently correct results. Is there a known workaround, such as a specific "Mode" or a hidden advanced setting that influences the linguistic pipeline? Alternatively, has anyone performed a comparative benchmark and found a superior alternative for Spanish technical content? My next steps are to instrument a formal benchmark against OpenAI's API, Claude, and a locally hosted Llama model fine-tuned on technical Spanish, but I wanted to gather practical data from user experiences first.