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Gen AI document data extraction and memorization in DB

Service description

We offer AI-powered solutions to optimize document processing by automating data extraction and structured storage in databases. Leveraging Generative AI, this service reduces manual effort, enhances data accuracy, and accelerates access to critical information, driving operational efficiency.
Expected results: Increased accuracy in data extraction, reduced manual effort, faster access to structured information, improved data management, and streamlined decision-making processes.
Methodology: Assessment: Analyze the current document data management process to identify manual steps, data accuracy, and storage inefficiencies.
Document Collection: Identify the document types and sources for data extraction.
AI Model Development: Train Generative AI models to extract relevant information from documents.
Data Structuring: Convert extracted data into structured formats for easy storage in databases.
Integration: Automate the data extraction and storage process to reduce manual effort.
Continuous Learning: Continuously refine AI models to improve accuracy and data handling over time.
Target: Manufacturing & Automotive
  • Organisation: REPLY
  • Type: Experiment
  • SUT/E: Rag Systems based on Gen AI
  • Average duration: 4.0 -- 6.0 months
  • Contact: m.diflorio@reply.it

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Co-Funded by the European Union Under grant agreement number 101100707

Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the Directorate-General for Communications Networks, Content and Technology. Neither the European Union nor the granting authority can be held responsible for them.

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