Using AI to convert unstructured information to structured information

Great insights! I really liked the way you explained this topic. For anyone exploring AI tools, I recommend checking out <a href="https://fiske.ai">Fiske ai image generator</a> — it’s super helpful for content creation. 

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Well yes, but I think it best consider that AI generative data be more used solely for customary changes. Also the person refrain from a comment on a different forum "as there crutch". Like I still do lots writing on physical notebook or sketchbooks. Up to individual on what floats they're boat.

The structured pipelines that store and compile data like SQL, SEO, or any of those can do a lot it always seems it's not enough. Goes along with lot of censorship that I don't find very pleasing or auctually in some derogatory. That's why it's important to convey a discernable truth. 

This is a very relevant and powerful use case — and you're definitely on the right track by exploring Co-Pilot Studio. From what we’ve seen at AIChief, converting unstructured data into structured formats requires a hybrid approach of AI + traditional data processing pipelines.

Here’s a recommended tech stack for your use case:

 Azure Form Recognizer / Document Intelligence – Excellent for extracting key-value pairs, tables, and layout data from PDFs, Word, and images.

Power Automate + AI Builder – Good for automating workflows, but can be limiting for complex document types. Can still be used to trigger processes post-extraction.

 Azure OpenAI or Azure Cognitive Services (via LangChain) – Use GPT-powered models to extract or infer structured data from semi-structured formats, especially where templates vary.

 Dataverse / SQL / Cosmos DB – For storing the extracted structured data and enabling analytics or visualization downstream.

If you're looking to scale this for enterprise use, consider layering a custom GPT or Co-Pilot model trained on your specific document formats.

We’ve published tools and curated insights at AIChief.com to help AI builders and teams working with similar automation use cases. Happy to connect or help further if needed!

This is a very relevant and powerful use case — and you're definitely on the right track by exploring Co-Pilot Studio. From what we’ve seen at AIChief, converting unstructured data into structured formats requires a hybrid approach of AI + traditional data processing pipelines.

Here’s a recommended tech stack for your use case:

✅ Azure Form Recognizer / Document Intelligence – Excellent for extracting key-value pairs, tables, and layout data from PDFs, Word, and images.

✅ Power Automate + AI Builder – Good for automating workflows, but can be limiting for complex document types. Can still be used to trigger processes post-extraction.

✅ Azure OpenAI or Azure Cognitive Services (via LangChain) – Use GPT-powered models to extract or infer structured data from semi-structured formats, especially where templates vary.

✅ Dataverse / SQL / Cosmos DB – For storing the extracted structured data and enabling analytics or visualization downstream.

If you're looking to scale this for enterprise use, consider layering a custom GPT or Co-Pilot model trained on your specific document formats.

We’ve published tools and curated insights at https://aichief.com to help AI builders and teams working with similar automation use cases. Happy to connect or help further if needed!

For converting unstructured information to structured data, you can use a combination of tools and technologies. AI Builder is a good starting point for extracting data from documents. If you encounter limitations, consider using Azure Form Recognizer for more advanced extraction capabilities. Additionally, Power Automate can help automate the process, and Azure Cognitive Services can provide enhanced processing capabilities. Storing and managing the structured data in Dataverse or Azure Synapse can also be beneficial. This combination of tools can help streamline the process and improve accuracy.

For extracting and structuring data from Excel, PDF, and Word, You should use these platforms ike Azure Form Recognizer, Power Automate, and Copilot Studio for automation. If AI Builder don't work, use Azure Cognitive Services or Python (Pandas, PyPDF2, OpenPyXL) for better control. Storing data in Dataverse or Synapse can help you in structuring data.

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For converting unstructured information to structured information, Azure Form Recognizer is a great tool for extracting data from documents. You can also use Power Automate for automation and explore Azure Cognitive Services for additional capabilities. These tools can help streamline the process and improve accuracy.

Converting unstructured information to structured data is a common challenge. AI Builder is a good starting point, but if you're exploring other options, consider using Azure Cognitive Services for document processing. The Form Recognizer service can extract text, key-value pairs, and tables from documents. For more complex scenarios, you might explore custom machine learning models using Azure Machine Learning or leveraging pre-trained models in the Azure OpenAI Service. Ensure you preprocess the data appropriately and consider using a combination of techniques for optimal results.

Hi Rahul 

I think you're essentially looking for a model that can understand the sementic meaning of the data, not just the literal text and its position on the page. 
You Can fine-tune an LLM ( like those in Azure OpenAI Service, or open-source modules like BERT) also You could train the LLM on a dataset of documents where you've manually labeled the "diameter" field, even when it's expressed differently. The LLM would then learn to identify the "diameter" field in new, unseen documents, even if the wording is slightly different.

Consider a knowledge Graph if you have a complex domain with many related concepts, a knowledge graph can be very helpful. 

hope this help 

For extracting structured data from Excel, PDF, and Word, consider Azure Form Recognizer, Power Automate, and Copilot Studio for automation. If AI Builder falls short, use Azure Cognitive Services or Python (Pandas, PyPDF2, OpenPyXL) for better control. Storing data in Dataverse or Synapse can help with structuring.

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