Troubleshoot missing answers and handle extraction failures
Match symptoms to causes for missing answers in Duale AI, and handle extraction failures by uploading checked text or reporting the document.
This page covers troubleshooting missing answers, extracting critical documents manually, and reporting documents that extract badly.
- Troubleshooting missing answers and early-stopped responses.
- Extracting critical documents yourself and uploading checked text.
- Reporting a document that extracts badly to support.
Summaries were generated by AI.
Start from the symptom that the answer or the Dashboard shows. Between tries, keep the Agent Identity, question, instructions, and model-pool configuration unchanged. Recovery means that the expected string or passage appears and the answer no longer reports that it stopped early.
Troubleshoot a missing answer
Extract a critical document yourself, then upload the text
Use it when a document has to be exactly right. Examples include a complex chart, a dense statistical figure, an engineering diagram, or a scan. Also use it when meaning sits in the relationships between parts rather than in the sentences.
What you get. You upload a human-checked text source and retain the comparison evidence before a Task depends on it. This reduces extraction risk; it does not prove what the model later retrieves or what it answers.
Duale AI tries to extract text and pictures from each supported document you upload. Extraction is best effort, not a fidelity guarantee, and the gap is widest where the meaning is visual. A chart carries its meaning in the relationship between an axis and a series. A statistical table carries it in the alignment of rows and columns. Those survive extraction less reliably than a paragraph does.
Two facts make this pattern work:
- Prefer a source that already contains text. Duale AI can read words directly from
.md,.txt,.docx, and Apple Pages files. A scan or an image of a diagram relies on OCR and visual extraction. A PDF can contain text, pixels, or both. - Review critical visual content separately. A person can check the relationships between labels, numbers, rows, columns, and pictures against the rendered source. This takes more work, so reserve it for documents where an extraction error changes an outcome.
Do this:
- Extract the document outside Duale AI
Use a person or a specialized extraction tool that reads the rendered page and writes out its content.
- Check the extraction against the original
Have a person compare them. The question is not whether the text reads well. It is whether every number, label, relationship, and caption still says what the original said.
- Upload the checked text version
Save it as Markdown, plain text, or a word-processor document, and upload that instead of the original.
- Check one known passage end to end
Ask for a value that appears only in the hardest checked passage. A correct answer checks that passage in that document version; it does not prove complete extraction or future answers.
Keep the original file wherever you keep your records. This pattern changes what your Tasks read, not what your organization holds.
Report a document that extracts badly
Use it when you find a document whose extracted text does not carry what the original said, and you would rather Duale AI read it correctly than work around it.
What you get. A report with enough evidence for support to reproduce the problem, plus checked text that keeps your Task moving while support investigates.
Duale AI owns the extraction path, so a specific failing document gives the team evidence it can act on.
- Confirm what extraction lost
Open the document preview in the Dashboard and compare it with the original. Record text that is wrong or missing, not text that the preview merely shortens.
- Record the minimum evidence
Note the document identifier, file name, file type, and the expected and observed text. Include the
request_idwhen an error response provides one. - Send the report to technical support
Email contact+support@mail.duale.ai with the evidence. Do not attach a sensitive source to ordinary email. Ask support for a secure transfer method if the team needs the original.
- Upload checked text as a temporary source
Follow the pattern above, then ask a question that depends on the missing content. A correct answer checks that question against the temporary source; it does not prove complete extraction or future answers.
If the checked text still gives a wrong or incomplete answer, compare its Dashboard preview with what you uploaded, then use the recovery table.