LegalTech Inc. Launches "AI Pre-Investigation Organization Workflow" for Chemical Manufacturers, Utilizing "IPGenius" AI Knowledge Base for Intellectual Property and R&D
Key facts
- LegalTech Inc. Launches "AI Pre-Investigation Organization Workflow" for Chemical Manufacturers, Utilizing "IPGenius" AI Knowledge Base for Intellectual Property and R&D
- LegalTech Inc. has launched the "AI Pre-Investigation Organization Workflow" for chemical manufacturers, powered by its AI knowledge base for intellectual property and R&D, "IPGenius." This workflow aims to streamline information organization, a prerequisite for prior art and FTO searches, by using AI to process patent specifications and experimental data. It extracts evaluated formulations and conditions from examples and comparative examples, and organizes material names to enhance search efficiency, assist in creating search term candidates, and organize internal technology configurations.
- Source: PR Times
- Date: June 12, 2026
Direct answer
LegalTech Inc. has launched the "AI Pre-Investigation Organization Workflow" for chemical manufacturers, powered by its AI knowledge base for intellectual property and R&D, "IPGenius." This workflow aims to streamline information organization, a prerequisite for prior art and FTO searches, by using AI to process patent specifications and experimental data. It extracts evaluated formulations and conditions from examples and comparative examples, and organizes material names to enhance search efficiency, assist in creating search term candidates, and organize internal technology configurations.
- Citation
- LegalTech Inc. Launches "AI Pre-Investigation Organization Workflow" for Chemical Manufacturers, Utilizing "IPGenius" AI Knowledge Base for Intellectual Property and R&D (June 12, 2026), PR Times
- Source
- PR Times
- Date
- June 12, 2026
LegalTech Inc. has launched the "AI Pre-Investigation Organization Workflow" for chemical manufacturers, powered by its AI knowledge base for intellectual property and R&D, "IPGenius." This workflow aims to streamline information organization, a prerequisite for prior art and FTO searches, by using AI to process patent specifications and experimental data. It extracts evaluated formulations and conditions from examples and comparative examples, and organizes material names to enhance search efficiency, assist in creating search term candidates, and organize internal technology configurations.
📋 Article Processing Timeline
- 📰 Published: June 12, 2026 at 23:00
- 🔍 Collected: June 12, 2026 at 14:21
- 🤖 AI Analyzed: June 12, 2026 at 16:51 (2h 30m after Collected)
LegalTech Inc. (Minato-ku, Tokyo; Representative Director: Tomoyuki Hirai) has launched the "AI Pre-Investigation Organization Workflow" for chemical manufacturers within its AI knowledge base for intellectual property and R&D, "IPGenius."
This workflow utilizes AI to organize patent specifications, experimental data, research notes, and table data of examples/comparative examples in the chemical field, supporting the information organization that serves as a prerequisite for prior art searches and FTO (Freedom-to-Operate) searches.
Specifically, it extracts formulations and conditions that were evaluated from examples and comparative examples, and organizes material names, product names, and abbreviations into generic names, chemical names, and higher concepts. This streamlines the creation of search term candidates, the organization of one's own technology configurations, and cross-searching of past cases.
Background: The Burden of Pre-Investigation Organization in the Chemical Field
In the R&D and IP operations of chemical manufacturers, diverse materials and formulation conditions such as resins, fillers, additives, curing agents, solvents, pigments, and functional materials are described in patent specifications and experimental data.
However, practical work involves the following tasks:
- Extracting the actually evaluated formulations from examples and comparative examples.
- Organizing material names, product names, abbreviations, and model numbers.
- Identifying generic names, chemical names, and higher concepts to be used for searches.
- Decomposing one's own technology configurations into a format comparable to competitors' patents.
- Checking for similar formulations or検討 (consideration/examination) cases in the past.
While these tasks are crucial as a prerequisite for prior art searches and FTO searches, they tend to depend on the experience and knowledge of the person in charge, often leading to variations in the granularity of organization and search perspectives.
What the "AI Pre-Investigation Organization Workflow" for Chemical Manufacturers Can Do
1. Extraction of Evaluated Formulations and Conditions
Extracts the formulations and conditions that were evaluated from examples, comparative examples, test examples, and table data described in patent specifications and experimental data.
Examples of information targeted:
- Names of each material
- Formulation ratios
- Units for formulation ratios
- Examples/comparative examples that were evaluated
- Evaluation items
- Evaluation results
- Condition differences
This enables organization focused on the formulations actually evaluated, rather than candidate components broadly listed in the specifications.
2. Organization of Nomenclature for Material Names, Product Names, and Abbreviations
In the chemical field, the same material may be described using multiple names, such as product names, abbreviations, generic names, chemical names, or manufacturer-specific names.
This workflow organizes potential nomenclature based on the material names described in the experimental data, including:
- Generic names
- Chemical names
- Higher concepts
- Alternative names
- Similar material names
- Substitute material names
This helps prevent search omissions caused by searching only by product name or abbreviation, and supports the creation of search term candidates for prior art and FTO searches.
3. Pre-processing for Prior Art and FTO Searches
Accurately decomposing the technology to be searched is crucial for prior art and FTO searches.
This workflow organizes and converts material formulations, constituent elements, applications, physical properties, effects, and evaluation conditions into a format suitable for investigation.
Use Cases:
- Pre-organization for prior art search of resin compositions
- Organization of formulations for adhesives, paints, inks, and coating materials
- Organization of material compositions including fillers, additives, and curing agents
- Organization of constituent elements before FTO search for one's own products
- Checking competitor patents when changing materials or formulations
- Cross-searching past investigation memos and similar cases
Difference from General-Purpose Generative AI
General-purpose generative AIs like ChatGPT, Gemini, and Copilot can summarize and extract from individual files.
However, IPGenius can be utilized as a knowledge base that can be reused within an organization by continuously accumulating IP and R&D data, combining it with business prompts, RAG search, source display, access control, and past case search.
Its characteristic feature is not just single-file AI utilization, but the ability to cross-search and organize past specifications, experimental data, investigation memos, and research notes, integrating them into the IP and R&D workflow.
About IPGenius
IPGenius is an AI knowledge base for IP and R&D departments.
It organizes IP and R&D data accumulated within a company, such as patent documents, technical memos, invention proposals, experimental reports, quality data, and design data, into a format that is easy to utilize with AI.
Main Application Areas:
- Cross-searching past documents
- Extracting and organizing invention candidates
- Organizing information before patent searches
- Organizing constituent elements before FTO searches
- Analyzing patent lists
- Knowledge creation from R&D data
Future Development
LegalTech Inc. plans to sequentially expand its AI workflows to accommodate the R&D and IP practices of various industries, including materials, chemicals, food, cosmetics, and electronic materials.
Following the workflow for chemical manufacturers, the company will develop templates tailored to the specific data formats, material names, evaluation items, and search perspectives of each industry, supporting prior art searches, FTO searches, invention extraction, and past case searches.
Product Page: https://www.legaltech.co.jp/ipgenius/
Company Profile
Company Name: LegalTech Inc.
Established: March 2021
Capital: 379 million yen (including capital reserve)
Representative Director President: Tomoyuki Hirai
Location: Toranomon 40MT Bldg. 4F, 5-13-1 Toranomon, Minato-ku, Tokyo
URL: https://www.legaltech.co.jp/
Business Overview
- Patent Search and Invention Extraction Platform "MyTokkyo.Ai"
- Knowledge Asset Base "AI IPGenius"
- Confidential Information Sharing Data Room "LegalTech VDR"
This workflow utilizes AI to organize patent specifications, experimental data, research notes, and table data of examples/comparative examples in the chemical field, supporting the information organization that serves as a prerequisite for prior art searches and FTO (Freedom-to-Operate) searches.
Specifically, it extracts formulations and conditions that were evaluated from examples and comparative examples, and organizes material names, product names, and abbreviations into generic names, chemical names, and higher concepts. This streamlines the creation of search term candidates, the organization of one's own technology configurations, and cross-searching of past cases.
Background: The Burden of Pre-Investigation Organization in the Chemical Field
In the R&D and IP operations of chemical manufacturers, diverse materials and formulation conditions such as resins, fillers, additives, curing agents, solvents, pigments, and functional materials are described in patent specifications and experimental data.
However, practical work involves the following tasks:
- Extracting the actually evaluated formulations from examples and comparative examples.
- Organizing material names, product names, abbreviations, and model numbers.
- Identifying generic names, chemical names, and higher concepts to be used for searches.
- Decomposing one's own technology configurations into a format comparable to competitors' patents.
- Checking for similar formulations or検討 (consideration/examination) cases in the past.
While these tasks are crucial as a prerequisite for prior art searches and FTO searches, they tend to depend on the experience and knowledge of the person in charge, often leading to variations in the granularity of organization and search perspectives.
What the "AI Pre-Investigation Organization Workflow" for Chemical Manufacturers Can Do
1. Extraction of Evaluated Formulations and Conditions
Extracts the formulations and conditions that were evaluated from examples, comparative examples, test examples, and table data described in patent specifications and experimental data.
Examples of information targeted:
- Names of each material
- Formulation ratios
- Units for formulation ratios
- Examples/comparative examples that were evaluated
- Evaluation items
- Evaluation results
- Condition differences
This enables organization focused on the formulations actually evaluated, rather than candidate components broadly listed in the specifications.
2. Organization of Nomenclature for Material Names, Product Names, and Abbreviations
In the chemical field, the same material may be described using multiple names, such as product names, abbreviations, generic names, chemical names, or manufacturer-specific names.
This workflow organizes potential nomenclature based on the material names described in the experimental data, including:
- Generic names
- Chemical names
- Higher concepts
- Alternative names
- Similar material names
- Substitute material names
This helps prevent search omissions caused by searching only by product name or abbreviation, and supports the creation of search term candidates for prior art and FTO searches.
3. Pre-processing for Prior Art and FTO Searches
Accurately decomposing the technology to be searched is crucial for prior art and FTO searches.
This workflow organizes and converts material formulations, constituent elements, applications, physical properties, effects, and evaluation conditions into a format suitable for investigation.
Use Cases:
- Pre-organization for prior art search of resin compositions
- Organization of formulations for adhesives, paints, inks, and coating materials
- Organization of material compositions including fillers, additives, and curing agents
- Organization of constituent elements before FTO search for one's own products
- Checking competitor patents when changing materials or formulations
- Cross-searching past investigation memos and similar cases
Difference from General-Purpose Generative AI
General-purpose generative AIs like ChatGPT, Gemini, and Copilot can summarize and extract from individual files.
However, IPGenius can be utilized as a knowledge base that can be reused within an organization by continuously accumulating IP and R&D data, combining it with business prompts, RAG search, source display, access control, and past case search.
Its characteristic feature is not just single-file AI utilization, but the ability to cross-search and organize past specifications, experimental data, investigation memos, and research notes, integrating them into the IP and R&D workflow.
About IPGenius
IPGenius is an AI knowledge base for IP and R&D departments.
It organizes IP and R&D data accumulated within a company, such as patent documents, technical memos, invention proposals, experimental reports, quality data, and design data, into a format that is easy to utilize with AI.
Main Application Areas:
- Cross-searching past documents
- Extracting and organizing invention candidates
- Organizing information before patent searches
- Organizing constituent elements before FTO searches
- Analyzing patent lists
- Knowledge creation from R&D data
Future Development
LegalTech Inc. plans to sequentially expand its AI workflows to accommodate the R&D and IP practices of various industries, including materials, chemicals, food, cosmetics, and electronic materials.
Following the workflow for chemical manufacturers, the company will develop templates tailored to the specific data formats, material names, evaluation items, and search perspectives of each industry, supporting prior art searches, FTO searches, invention extraction, and past case searches.
Product Page: https://www.legaltech.co.jp/ipgenius/
Company Profile
Company Name: LegalTech Inc.
Established: March 2021
Capital: 379 million yen (including capital reserve)
Representative Director President: Tomoyuki Hirai
Location: Toranomon 40MT Bldg. 4F, 5-13-1 Toranomon, Minato-ku, Tokyo
URL: https://www.legaltech.co.jp/
Business Overview
- Patent Search and Invention Extraction Platform "MyTokkyo.Ai"
- Knowledge Asset Base "AI IPGenius"
- Confidential Information Sharing Data Room "LegalTech VDR"
FAQ
What kind of problems does this AI workflow solve?
It resolves the burden of extracting evaluated formulations/conditions and organizing material names from patent specifications and experimental data for chemical manufacturers, as well as inconsistencies due to experience-based variations.
What is IPGenius?
It is a knowledge base that organizes IP and R&D data into an AI-usable format for reuse within an organization, enabling cross-searching of past documents and extraction of invention candidates.
How does it differ from general-purpose AI?
General AI is suited for individual file processing, whereas IPGenius is a knowledge base for continuous data accumulation and organizational use, allowing integration into business processes.
What kind of investigative tasks is it useful for?
It streamlines the pre-processing for prior art and FTO searches by extracting evaluated formulations/conditions, organizing material nomenclature, and converting data into a usable format for investigation.
What are the future plans?
Following the chemical sector, the company plans to sequentially expand AI workflows tailored to the needs of various industries, including materials, food, cosmetics, and electronic materials.