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Source Normalizer

Transform data (PDFs, Word files, spreadsheets, text, recordings and images) in a uniform Markdown format.

How to use the Source Normalizer

  1. 1Add the sourcesPDFs, Word files, spreadsheets, text, recordings and images, or start from a ready-made set.
  2. 2Label themMark each file primary (first-hand evidence) or secondary (background).
  3. 3NormalizeEach file becomes Markdown that keeps its file name and label. Progress shows file by file.
  4. 4Explore and use the textsSearch across all texts, read them, fix errors, then download them or send them to the Knowledge Curator.
  • Documents are converted locally. Only recordings and images call a model. A scanned PDF with no text layer stops the run, and recordings carry no timestamps for each utterance.
  • The result lives in this browser tab. Reloading or closing the tab loses it, so download the .zip first.

Start from a ready-made set of sources

1. The sources
Up to 20 files, 100 MB together. File names must be unique.

Click primary or secondary to switch a label. Primary sources are your own first-hand evidence, such as site notes or recordings. Secondary sources are background, such as older reports. Not supported: PowerPoint (.pptx), old Office formats (.doc, .xls), scanned PDFs without a text layer.

2. Options
Only recordings and images call a model. The other files are converted locally, whatever you choose here.

The language of the speech in the recordings, or a language code of your own.

Leave it empty to use the server's transcription model.

Leave it empty to use the server's model for describing images.

No result yet

Load a ready-made set or add files, then click Normalize. The texts appear here, where you can search all of them at once.

GAIK Toolkit

Generative AI building blocks for knowledge capture, access and synthesis.

Co-funded by the European Union

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Disclaimer: The demo website uses Microsoft Azure APIs for OpenAI's and Anthropic's models, and Google's Vertex AI for Gemini models. No user data is retained, and neither Azure nor Vertex AI uses any user data for model training.

© 2026 GAIK ProjectThe gaik package is open source under the MIT licence.
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