Text data preparation
This guide walks you through preparing the text content needed to add a new language to your AI Agent. Follow each step in order.
Step 1 – Gather your source content
Collect all existing material that covers the topics your AI Agent should be able to answer. This can include:
FAQs
Policies and procedures
Customer support scripts
Website content
Product documentation
Keep everything in English at this stage. Do not translate yet.
Once collected, clean the content:
Remove duplicate information
Fix formatting issues
Make sure answers are clear and complete
Fill in any gaps – if a topic is missing that users are likely to ask about, add it now
Step 2 – Organise your content into topics
For each topic your AI Agent should handle, define three things:
Topic – a short label for the subject (e.g. "Account registration")
Answer – the exact response the AI Agent will give
Questions – 10 to 15 different ways a user might ask about that topic
Why questions matter most: The AI Agent learns to recognise what a user is asking by matching their message against these example questions. Without at least 10 varied questions per topic, the AI Agent cannot reliably route users to the correct response.
Example:
Topic
Account registration
Answer
To register an account, visit our website and select Sign up in the top right corner. You will need your national ID number, a valid email address, and a phone number. Registration takes approximately five minutes.
Question 1
How do I sign up?
Question 2
How can I create an account?
Question 3
What do I need to register?
Question 4
I want to open an account
Question 5
Where do I go to register?
Tips for writing good questions:
Write questions the way real users would – natural, not formal
Vary the phrasing significantly, not just minor word swaps. "How do I sign up?" and "How can I sign up?" are essentially the same question – find genuinely different ways to ask
Cover different levels of formality and the different ways people frame the same request
You can use an AI tool to help generate question variations with a prompt such as: "Generate 10–15 different ways a user might ask: [your question here]."
Work in batches of 10 topics at a time. Review each batch before moving to the next.
Step 3 – Check for duplicates
Before translating, review the full dataset to ensure no question appears under more than one topic. If the same question maps to two different topics, the AI Agent will not know which response to give.
Example of a problem to fix: "How do I check my balance?" should not appear under both "Account balance" and "Loan balance." Assign it to one topic only and remove it from the other.
Review checklist:
✅ Every topic has a clear, accurate answer
✅ Every topic has at least 10 questions
✅ No question appears under more than one topic
✅ Questions are varied and natural – not just minor rephrasings of each other
✅ All topics a user is likely to ask about are covered
Step 4 – Translate the dataset
Work through the dataset column by column, translating each question and answer one at a time.
Instructions for the translator:
Translate one sentence at a time – do not merge or combine sentences
Stay aligned with the original row and ID numbers
Aim for natural phrasing – translate the meaning, not word for word
Do not remove or skip any questions
If a term has no direct equivalent in the target language, use the term your audience would naturally use – and flag it with a note for review
Output format:
001
Topic
Account registration
[Translation]
002
Answer
To register an account, visit our website...
[Translation]
003
Question
How do I sign up?
[Translation]
004
Question
How can I create an account?
[Translation]
Step 5 – Submit your dataset
Once translation is complete, submit the following to your Proto contact:
✅ Reference documents (English source material) ✅ Completed Q&A dataset (English + translated) ✅ Glossary of key terms (optional, but recommended for specialised vocabulary)
Common mistakes to avoid
Translating before structuring
Raw translated content cannot be used to configure the AI Agent – structure must come first
Providing raw documents instead of Q&A format
The AI Agent cannot use unstructured content
Fewer than 10 questions per topic
The AI Agent will not reliably recognise that topic
Questions that are too similar to each other
Reduces the range of real user messages the AI Agent can match
Skipping or merging questions during translation
Breaks the dataset and causes rework
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