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  6. Development of a generative AI system for multimodal input.

Development of a generative AI system for multimodal input.

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LLFarM

last updated:Mar 04, 2026

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Images, PDFs, Excel, Word, and PowerPoint can all be input into the LLM.

We are developing a generative AI system with multimodal input. We perform preprocessing according to data types and accurately retrieve necessary information from the LLM. We can assist with specification determination or issue extraction. We can create a system tailored to your needs in a short time and at a low cost.

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WEBFARMERさま_納品_縦02_トリミング済みの_280x280.png

Development of a generative AI system for multimodal input.

WEBFARMERさま_納品_縦02_トリミング済みの_280x280.png
WEBFARMERさま_納品_縦02_トリミング済みの_280x280.png
  • Related Link - https://web-farmer.net/work/aiエージェントを用いて動的にプラニングする…

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basic information

【Input Data Types】 - Image - Video - PDF - EXCEL - WORD - POWERPOINT 【Information to be Obtained】 - Written text - Image information (including each element on the image and their relationships) - Table information - Special symbols, etc. 【LLM to be Used】 - GPT - Gemini - Others 【Cloud to be Used】 - Azure - AWS - GCP - Others

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Applications/Examples of results

July 2025 - Developed a certain type of idea generation system - Built the system on the customer's local computer - Limited usage within a constrained budget and provided support - Compatible with Excel and Word November 2025 - Developed a system to extract information from a certain type of document - Built on Azure, utilizing GPT and Gemini - Addressed as a proof of concept (POC) in a short period - Compatible with Excel, Word, and PDF March 2026 - Developed a system using generative AI - Built on Azure, utilizing GPT and others - Continuously developed as POC1 and POC2 - Compatible with images, videos, Excel, Word, and PDF

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LLFarM - LLM Solutions for Web Farmers -

LLFarM - LLM Solutions for Web Farmers -

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Our company is engaged in various artificial intelligence development businesses, including artificial intelligence consulting, artificial intelligence seminars, and artificial intelligence application development. Since 2013, we have shifted to Deep Learning, working on improvements to CNNs and RNNs, and by 2015, we developed our own model using RNNs. Additionally, starting in 2016, we expanded our focus to deep reinforcement learning, developing numerous simulation models and robot models. Please feel free to contact us if you have any inquiries.

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