{"id":7,"date":"2025-12-20T21:39:59","date_gmt":"2025-12-20T12:39:59","guid":{"rendered":"http:\/\/www.mindware.llc\/?page_id=7"},"modified":"2026-07-22T15:58:52","modified_gmt":"2026-07-22T06:58:52","slug":"home","status":"publish","type":"page","link":"https:\/\/www.mindware.llc\/en\/home\/","title":{"rendered":""},"content":{"rendered":"\n<meta charset=\"utf-8\"><meta name=\"viewport\" content=\"width=device-width,initial-scale=1\"><title>Mindware Multi-Client Development Project | Building a Self-Organizing Operational World Model<\/title><meta name=\"description\" content=\"An early-participation multi-client development program integrating organizational knowledge mining, episodic memory, and process mining to build enterprise-governed Operational World Models.\"><meta property=\"og:title\" content=\"Mindware Multi-Client Development Project | Building a Self-Organizing Operational World Model\"><meta property=\"og:description\" content=\"An early-participation multi-client 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.mw-research-row h3{padding-top:5px;padding-bottom:8px}}\n<\/style><div class=\"mw-site-owm\" id=\"top\">\n<header class=\"mw-header\"><div class=\"mw-wrap mw-header__inner\"><a class=\"mw-brand\" href=\"#top\">Mindware Project<small>Multi-Client Development Project<\/small><\/a><nav class=\"mw-nav\" id=\"mw-nav\" aria-label=\"Primary navigation\"><a href=\"#overview\">Overview<\/a><a href=\"#objective\">Objective<\/a><a href=\"#minimum\">Minimum Scope<\/a><a href=\"#deliverables\">Deliverables<\/a><a href=\"#participation\">Participation<\/a><a class=\"mw-nav__cta\" href=\"#contact\">Contact<\/a><\/nav><button class=\"mw-menu\" type=\"button\" aria-label=\"Open menu\" aria-controls=\"mw-nav\" aria-expanded=\"false\"><span><\/span><span><\/span><span><\/span><\/button><\/div><\/header>\n<main>\n<section class=\"mw-hero\" aria-labelledby=\"hero-title\"><div class=\"mw-wrap\"><div class=\"mw-docline\"><div class=\"mw-docline__name\">Mindware Multi-Client Development Project \u2014 Draft<\/div><div class=\"mw-docline__draft\">Phase 1 Development Plan (Draft)<\/div><\/div><p class=\"mw-hero__intro\">Enterprise adoption of AI agents will soon face a fundamental obstacle: LLMs cannot persistently retain company-specific knowledge, experience, and decision histories in a verifiable form. Larger context windows do not solve this problem. In the post-AI-bubble era, the central development challenge will shift toward building Operational World Models.<\/p><p class=\"mw-project-name\">Mindware Multi-Client Development Project<\/p><p class=\"mw-project-phase\">Phase 1 Development Plan (Draft)<\/p><p class=\"mw-title-prefix\">Building on LLM Wiki and Concept Index<\/p><h1 class=\"mw-main-title\" id=\"hero-title\">Building a Self-Organizing Operational World Model<br>through Organizational Knowledge Mining<\/h1><div class=\"mw-core-outcome\">Core Development Outcome: Integrated Organizational Knowledge Mining, Episodic Memory, and Process Mining<\/div><p class=\"mw-period\">Phase 1: October 1, 2026 &#8211; September 30, 2027<\/p><p class=\"mw-organizer\">Organizer: Mindware Research Institute, Inc.<\/p><div class=\"mw-flow-hero\"><div class=\"mw-flow-hero__box\">Operational Information<\/div><div class=\"mw-flow-hero__arrow\">\u2192<\/div><div class=\"mw-flow-hero__box\">Knowledge Mining<\/div><div class=\"mw-flow-hero__arrow\">\u2192<\/div><div class=\"mw-flow-hero__box\">Operational World Model<\/div><\/div><div class=\"mw-what\"><strong>What This Project Will Develop<\/strong><p>The system will ingest information scattered across internal documents, relational databases, operational logs, reports, and other sources; extract candidate elements with LLMs; support human validation; form concepts through ConceptMiner and Concept Index; and structure the results as Episode Cards and process models. The outcome will be an enterprise-governed Operational World Model shared by human users and AI agents.<\/p><\/div><dl class=\"mw-summary\"><div class=\"mw-summary__row\"><dt>Intended Participants<\/dt><dd>Executives and practitioners responsible for AI\/DX, information systems, R&amp;D, corporate planning, new business, and knowledge management across manufacturing, distribution, retail, telecommunications, IT, finance, food and beverage, and other industries<\/dd><\/div><div class=\"mw-summary__row\"><dt>Participation Fee<\/dt><dd>JPY 2.5 million per unit, excluding tax \/ up to two designated participants per unit<\/dd><\/div><div class=\"mw-summary__row\"><dt>Payment Terms<\/dt><dd>50% upon application and contract execution; 50% before the project begins<\/dd><\/div><div class=\"mw-summary__row\"><dt>Participation Format<\/dt><dd>Multiple units permitted; company and participant names confidential in principle<\/dd><\/div><div class=\"mw-summary__row\"><dt>Launch Condition<\/dt><dd>No minimum number of companies; the project will proceed from one participant<\/dd><\/div><div class=\"mw-summary__row\"><dt>Initial Expansion Target<\/dt><dd>20 companies; additional development, external specialists, and evaluation environments will expand with participation<\/dd><\/div><\/dl><div class=\"mw-actions\"><a class=\"mw-btn mw-btn--primary\" href=\"#objective\">View the Development Objective<\/a><a class=\"mw-btn mw-btn--secondary\" href=\"#participation\">View Participation Details<\/a><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"overview\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">01<\/div><h2 class=\"mw-section__title\">Project Overview<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">This is a one-year, multi-client development program in which participating companies jointly support the creation of a common software foundation that transforms documents, data, logs, conversation records, and decision histories scattered across an organization into reusable knowledge, experience, and process assets. The primary objective is not company-specific research or consulting, but the establishment of a reusable product foundation applicable across multiple organizations.<\/p><div class=\"mw-problem-list\"><div class=\"mw-problem-row\"><h3>Company-specific knowledge does not persist<\/h3><p>Chat histories and summaries do not become governed enterprise assets with source traceability, change history, access control, and outcome evaluation.<\/p><\/div><div class=\"mw-problem-row\"><h3>RAG alone cannot model operational reality<\/h3><p>Document retrieval cannot by itself represent who made what decision, under which circumstances, with what outcome, or how work proceeds through sequences and branches.<\/p><\/div><div class=\"mw-problem-row\"><h3>Analytical outputs are not operational artifacts<\/h3><p>Clusters and process maps are not enough. The system must produce manuals, case collections, decision rationales, and improvement candidates that business users can continue to use.<\/p><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"objective\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">02<\/div><h2 class=\"mw-section__title\">Development Objective: Building an Operational World Model through Organizational Knowledge Mining<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">The Operational World Model proposed here is not a massive model intended to simulate the world in general. It is an organization-specific model that continuously updates actors, objects, states, events, decisions, outcomes, relationships, and operating procedures with traceable sources.<\/p><div class=\"mw-definition\"><div class=\"mw-definition__top\"><div class=\"mw-definition__term\"><strong>Operational<br>World Model<\/strong><span>Model how the organization actually operates from dispersed operational information<\/span><\/div><div class=\"mw-definition__copy\">Rather than completing a fixed ontology in advance, the system forms concepts and structures from actual documents, data, and experience in a form that people can inspect and revise.<\/div><\/div><div class=\"mw-table mw-table--three\"><div class=\"mw-table__inner\"><div class=\"mw-table__row mw-table__head\"><div>Input Information<\/div><div>Mining and Structuring<\/div><div>Operational Assets Created<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Policies, manuals, reports, and meeting records<\/div><div class=\"\">Knowledge-page compilation, question-pattern generation, and source reference through LLM Wiki<\/div><div class=\"\">Searchable and reusable document knowledge<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Relational databases, CSV files, and free-text data<\/div><div class=\"\">Concept formation through embeddings, GNG + MST, and Concept Index<\/div><div class=\"\">Concept nodes, similarity groups, and conceptual segments<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Business systems and automation flows such as Zapier<\/div><div class=\"\">Normalize events, decisions, and outcomes and record them as Episode Cards<\/div><div class=\"\">Verifiable operational episodic memory<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Time-sequenced events, work histories, and response histories<\/div><div class=\"\">Event-log generation, process discovery, and analysis of deviations, repetitions, and handoffs<\/div><div class=\"\">Process models based on actual operations<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Human validation, evaluation, and correction<\/div><div class=\"\">Manage sources, change histories, permissions, and approval status<\/div><div class=\"\">A trustworthy knowledge foundation governed by the enterprise<\/div><\/div><\/div><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"cores\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">03<\/div><h2 class=\"mw-section__title\">Core Development Outcomes of Phase 1<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">Phase 1 will connect the following five outcomes as one information-flow and governance foundation rather than as isolated experiments.<\/p><div class=\"mw-core-grid\"><article class=\"mw-core-card\"><span class=\"mw-core-card__label\">CORE 01<\/span><h3>Organizational Knowledge Mining Core<\/h3><p>Extract candidate actors, actions, objects, states, decisions, and outcomes from documents, free text, operational data, and logs, then convert validated candidates into reusable knowledge units.<\/p><\/article><article class=\"mw-core-card\"><span class=\"mw-core-card__label\">CORE 02<\/span><h3>Episode Memory Core<\/h3><p>Accumulate situations, events, decisions, outcomes, evaluations, and sources as Episode Cards and retrieve related experience for reuse.<\/p><\/article><article class=\"mw-core-card\"><span class=\"mw-core-card__label\">CORE 03<\/span><h3>Process Mining Core<\/h3><p>Transform structured logs and human-validated event candidates from unstructured information into models of actual workflows, exceptions, rework, and branching paths.<\/p><\/article><article class=\"mw-core-card\"><span class=\"mw-core-card__label\">CORE 04<\/span><h3>Operational World Model Layer<\/h3><p>Provide a common schema and reference APIs linking document knowledge, concept nodes, episodes, processes, sources, and permissions for continuous updating.<\/p><\/article><article class=\"mw-core-card\"><span class=\"mw-core-card__label\">CORE 05<\/span><h3>Business Artifact Generator<\/h3><p>Convert analytical outputs into drafts of operating manuals, process descriptions, case collections, decision rationales, and improvement candidates.<\/p><\/article><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"workflow\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">04<\/div><h2 class=\"mw-section__title\">Core Workflow Enabled by the Completed System<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-step-list\"><div class=\"mw-step\"><div class=\"mw-step__n\">1<\/div><p>Ingest documents, data, logs, and events from business systems, relational databases, files, and automation tools such as Zapier.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">2<\/div><p>Preserve source information such as original text, record IDs, timestamps, authors, and system names for later verification.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">3<\/div><p>Use LLMs as language-processing components to extract and normalize candidate actors, actions, objects, states, decisions, outcomes, reasons, and evaluations.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">4<\/div><p>Allow human reviewers to validate candidates, correct errors, add evaluations, approve content, and define access scopes.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">5<\/div><p>Generate knowledge pages, Episode Cards, event logs, and process descriptions from validated information.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">6<\/div><p>Use ConceptMiner and Concept Index to form conceptual groupings, and process mining to identify actual flows, exceptions, rework, and branching paths.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">7<\/div><p>Enable business users to work with the results as manuals, case collections, and process models, while AI agents retrieve relevant knowledge and experience through MCP or APIs.<\/p><\/div><div class=\"mw-step\"><div class=\"mw-step__n\">8<\/div><p>Record new decisions and outcomes and continuously update the organization-specific knowledge, experience, and process models.<\/p><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"minimum\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">05<\/div><h2 class=\"mw-section__title\">Minimum Scope of the Phase 1 Reference Implementation<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">The project does not promise fully autonomous agents or automated strategic decision-making. Priority will be given to completing an implementation foundation that participating companies can inspect and evaluate themselves.<\/p><div class=\"mw-table mw-table--three\"><div class=\"mw-table__inner\"><div class=\"mw-table__row mw-table__head\"><div>Functional Area<\/div><div>Minimum Scope<\/div><div>Practical Significance<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Information Ingestion<\/div><div class=\"\">API and webhook input, CSV and JSON file input, and sample workflows for tools such as Zapier<\/div><div class=\"\">Capture operational information without relying exclusively on manual entry<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Source and Access Governance<\/div><div class=\"\">Original-source references, record IDs, timestamps, authors, access scopes, and basic change history<\/div><div class=\"\">Verify generated results and keep them under enterprise control<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">LLM Extraction and Normalization<\/div><div class=\"\">Extract candidate actors, actions, objects, states, decisions, outcomes, and reasons and convert them to a common format<\/div><div class=\"\">Turn fragmented natural-language information into an entry point for structuring<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Knowledge-Page and Document Generation<\/div><div class=\"\">Generate draft knowledge pages, operational descriptions, case summaries, and process explanations with links to source material<\/div><div class=\"\">Produce artifacts usable by people who are not data analysts<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Episode Card<\/div><div class=\"\">Create, edit, and delete records of situations, events, decisions, outcomes, evaluations, sources, authors, and timestamps<\/div><div class=\"\">Preserve experience as verifiable units rather than mere chat history<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Process Mining<\/div><div class=\"\">Event-log generation, basic process discovery, and visualization of frequency, paths, repetitions, and exceptions<\/div><div class=\"\">Understand how work is actually performed rather than relying only on prescribed procedures<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Concept Formation and Related-Information Discovery<\/div><div class=\"\">Attribute search, semantic similarity, concept nodes, and conceptual segments<\/div><div class=\"\">Discover groupings that emerge from the data, not only predefined classifications<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Human Governance<\/div><div class=\"\">Validation, correction, deletion, added evaluation, approval status, source reference, and basic change history<\/div><div class=\"\">Keep enterprise knowledge under human governance rather than delegating it entirely to AI<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">MCP \/ API Access<\/div><div class=\"\">Reference connections through which AI agents search and retrieve knowledge, episodes, concepts, and processes<\/div><div class=\"\">Avoid lock-in to a specific LLM or agent<\/div><\/div><div class=\"mw-table__row\"><div class=\"mw-table__title\">Evaluation and Deliverables<\/div><div class=\"\">Reference code, execution environment, setup instructions, API specifications, sample data, and evaluation scenarios<\/div><div class=\"\">Enable participating companies to conduct internal evaluations<\/div><\/div><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"usecases\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">06<\/div><h2 class=\"mw-section__title\">Illustrative Use Cases<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-usecases\"><article class=\"mw-usecase\"><h3>Quality and Maintenance<\/h3><p><strong>Information Ingested:<\/strong> Anomaly reports, equipment logs, causal hypotheses, responses, and recovery outcomes<\/p><p><strong>Outputs Generated and Used:<\/strong> Similar-incident cards, effective and ineffective responses, deviations from standard procedures, and draft maintenance manuals<\/p><\/article><article class=\"mw-usecase\"><h3>Research and Development<\/h3><p><strong>Information Ingested:<\/strong> Experimental conditions, design reviews, failures, decisions, outcomes, and next hypotheses<\/p><p><strong>Outputs Generated and Used:<\/strong> Recall of failure cases, hypothesis lineage, conceptual clustering of conditions, and reconstruction of experimental records<\/p><\/article><article class=\"mw-usecase\"><h3>Sales and Customer Service<\/h3><p><strong>Information Ingested:<\/strong> CRM records, sales-call notes, proposals, responses, and reasons for wins or losses<\/p><p><strong>Outputs Generated and Used:<\/strong> Similar customers and opportunities, win-loss factors, response processes, and draft proposal and service playbooks<\/p><\/article><article class=\"mw-usecase\"><h3>Manufacturing, Logistics, and Administrative Operations<\/h3><p><strong>Information Ingested:<\/strong> Work logs, application histories, emails, handoffs, and daily reports<\/p><p><strong>Outputs Generated and Used:<\/strong> Actual workflows, rework, delays, duplication, process documentation, and improvement candidates<\/p><\/article><article class=\"mw-usecase\"><h3>Management and New Business Development<\/h3><p><strong>Information Ingested:<\/strong> Meeting records, assumptions, options, decisions, execution outcomes, and evaluations<\/p><p><strong>Outputs Generated and Used:<\/strong> Decision histories, consistency with past policies, outcomes of similar decisions, and collections of decision rationales<\/p><\/article><article class=\"mw-usecase\"><h3>Skill and Knowledge Transfer<\/h3><p><strong>Information Ingested:<\/strong> Interviews with experienced personnel, scattered documents, cases, and tacit decision criteria<\/p><p><strong>Outputs Generated and Used:<\/strong> LLM Wiki pages, business processes, case collections, records of exception handling, and training drafts<\/p><\/article><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"why\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">07<\/div><h2 class=\"mw-section__title\">Why Enterprise AI Now Needs an Operational World Model<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-problem-list\"><div class=\"mw-problem-row\"><h3>01<\/h3><p>Large language models possess extensive general knowledge and language capabilities, but they do not preserve company-specific experience, decision criteria, or operational reality in a persistent and verifiable form.<\/p><\/div><div class=\"mw-problem-row\"><h3>02<\/h3><p>RAG and vector search are useful for locating document fragments, but they cannot by themselves model decision histories or the sequences and branches through which work actually proceeds.<\/p><\/div><div class=\"mw-problem-row\"><h3>03<\/h3><p>This project uses LLMs as standard components for extraction, summarization, verbalization, and dialogue. Its competitive focus is the mechanism that continuously turns enterprise observations into concepts, experience, and processes under human governance.<\/p><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"kdd\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">08<\/div><h2 class=\"mw-section__title\">Avoiding the Mistakes of the KDD and Data-Mining Era<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">Even a useful discovery algorithm becomes difficult to use when the distance between its output and a practical business artifact is too great. This project includes the conversion from discovery into documents, processes, and cases within the product itself.<\/p><div class=\"mw-lesson-grid\"><div class=\"mw-lesson-row mw-lesson-row--head\"><div>Design to Avoid<\/div><div>Design Adopted in This Project<\/div><\/div><div class=\"mw-lesson-row\"><div>Stop after displaying clusters or process maps<\/div><div>Generate drafts of knowledge pages, process descriptions, case collections, decision rationales, and improvement candidates<\/div><\/div><div class=\"mw-lesson-row\"><div>Require business users to interpret outputs without guidance<\/div><div>Provide industry- and function-specific templates, review items, and evaluation scenarios<\/div><\/div><div class=\"mw-lesson-row\"><div>Treat AI-generated content as established fact<\/div><div>Preserve original text, sources, change history, and approval status and require human validation<\/div><\/div><div class=\"mw-lesson-row\"><div>Depend on the skills of individual consultants<\/div><div>Productize the capability as common data models, reference implementations, APIs, and setup procedures<\/div><\/div><div class=\"mw-lesson-row\"><div>Evaluate through a one-time proof of concept<\/div><div>Evaluate a continuing cycle in which new events and outcomes update knowledge, experience, and process models<\/div><\/div><\/div><div class=\"mw-note\">Success will be evaluated not by the number of advanced algorithms included, but by reuse of past experience, reduced documentation time, traceability of decision rationales, and improvement of operational processes.<\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"foundation\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">09<\/div><h2 class=\"mw-section__title\">Existing Implementation Foundation<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">This project does not begin from zero. Since April 2025, Mindware Research Institute has developed and validated the following technologies as working systems.<\/p><div class=\"mw-foundation\"><div class=\"mw-foundation__row\"><h3>ThinkNavi \/ LLM Wiki<\/h3><span class=\"mw-status\">Implemented<\/span><p>Reconstructs documents as knowledge pages, routes questions to appropriate pages, and references source documents. Phase 1 will separate Single Wiki Builder and use it as the foundation for business-artifact generation.<\/p><\/div><div class=\"mw-foundation__row\"><h3>ConceptMiner<\/h3><span class=\"mw-status\">Implemented<\/span><p>Applies Growing Neural Gas and a Minimum Spanning Tree to embedding space to form concept nodes and relationship structures.<\/p><\/div><div class=\"mw-foundation__row\"><h3>Concept Index<\/h3><span class=\"mw-status\">In Development<\/span><p>Maps records in existing relational databases to concept nodes, enabling conceptual extraction through SQL and connecting operational data and episodes to the model.<\/p><\/div><div class=\"mw-foundation__row\"><h3>CCM \/ Thinking Support<\/h3><span class=\"mw-status\">Implemented<\/span><p>An experimental environment for associative responses and decision support using relationships among concepts, episodes, and decision candidates.<\/p><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"philosophy\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">10<\/div><h2 class=\"mw-section__title\">Core Philosophy: A Self-Organizing Concept Approach<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-philosophy\"><div class=\"mw-philosophy__head\"><h3>Grow concept structures from observed data instead of defining a fixed ontology first<\/h3><\/div><div class=\"mw-philosophy__body\"><p>Rules, objects, and ontologies are useful for system integration, regulatory compliance, and access control. However, predefined structures alone cannot cover new similarities, exceptions, ambiguous judgments, and organization-specific meanings. The project forms concept structures from actual data while people name and formalize only what must be fixed.<\/p><div class=\"mw-philosophy__formula\"><div class=\"mw-philosophy__box\"><strong>LLM<\/strong><span>Candidate extraction, summarization, documentation, and dialogue from natural language<\/span><\/div><div class=\"mw-philosophy__sign\">\uff0b<\/div><div class=\"mw-philosophy__box\"><strong>ConceptMiner \/ Concept Index<\/strong><span>Form concept nodes, segments, and relationship structures from similarity and relationships<\/span><\/div><div class=\"mw-philosophy__sign\">\uff0b<\/div><div class=\"mw-philosophy__box\"><strong>Process Mining<\/strong><span>Derive actual flows, branches, repetitions, and exceptions from time-sequenced events<\/span><\/div><div class=\"mw-philosophy__sign\">\uff0b<\/div><div class=\"mw-philosophy__box\"><strong>Human Validation and Governance<\/strong><span>Source verification, correction, approval, permissions, evaluation, and naming<\/span><\/div><\/div><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--navy\" id=\"deliverables\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">11<\/div><h2 class=\"mw-section__title\">Deliverables and Services for Participating Companies<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">Each participating company will receive the contractual foundation package regardless of participation scale. Twenty companies is not a launch condition; it is an expansion target for additional development and external review.<\/p><div class=\"mw-deliverables\"><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">01<\/div><h3>Organizational Knowledge Mining Core<\/h3><p>Reference implementation covering information ingestion, source governance, LLM-generated extraction candidates, human validation, and generation of knowledge units and event candidates.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">02<\/div><h3>Episode Memory Core<\/h3><p>Reference implementation including Episode Cards, related-case retrieval, API and webhook input, MCP and API access, and basic management functions.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">03<\/div><h3>Process Mining Core<\/h3><p>Reference implementation including event-log generation, basic process discovery, visualization of paths, repetitions, and exceptions, and sample evaluation scenarios.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">04<\/div><h3>Operational World Model Specification<\/h3><p>Common schema, API specifications, and sample data linking document knowledge, concepts, episodes, processes, sources, and permissions.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">05<\/div><h3>Single Wiki Builder<\/h3><p>Participant-only source code extracted from ThinkNavi, including access to a restricted GitHub repository, setup instructions, and sample data.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">06<\/div><h3>Concept Index<\/h3><p>Executable software and basic documentation for evaluating conceptual search. Supported operating systems, databases, and terms of use will be specified at delivery.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">07<\/div><h3>ThinkNavi \/ ConceptMiner Annual Usage Rights<\/h3><p>Usage and evaluation rights for designated functions during Phase 1. API charges, processing scale, and usage scope will be defined in the participation terms.<\/p><\/div><div class=\"mw-deliverable\"><div class=\"mw-deliverable__n\">08<\/div><h3>Year-Round Online Program<\/h3><p>Monthly sessions, technical demonstrations, development reports, an archive of recordings and materials, common-question support, and a final report.<\/p><\/div><\/div><div class=\"mw-guarantee\">There is no minimum launch threshold. The contracted foundation outcomes and minimum scope of each Core are planned regardless of participation scale.<\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"expansion\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">12<\/div><h2 class=\"mw-section__title\">Expansion According to Participation<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-expansion\"><div class=\"mw-expansion__item\">The foundation deliverables and minimum scope of each Core are planned regardless of the number of participating companies.<\/div><div class=\"mw-expansion__item\">Reaching 20 companies will serve as a benchmark for substantially expanding implementation, expert review, evaluation tools, and documentation.<\/div><div class=\"mw-expansion__item\">Advanced reflection, memory consolidation, case-based strategic judgment, conformance checking, predictive process monitoring, additional connectors, and multi-agent sharing will be selected according to participation and technical validation.<\/div><div class=\"mw-expansion__item\">Additional themes will be selected by the organizer as common technical issues rather than treated as ordinary one-company custom development requests.<\/div><div class=\"mw-expansion__item\">Company-specific proofs of concept, integrations, data preparation, and customization will be contracted separately from the annual participation fee.<\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"schedule\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">13<\/div><h2 class=\"mw-section__title\">Phase 1 Development Schedule (Draft)<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-timeline\"><div class=\"mw-time\"><h3>October-December 2026<\/h3><p><strong>Core Work:<\/strong> Participant interviews, common-use-case definition, information ingestion, and data-model design for sources, permissions, Episode Cards, and event candidates<\/p><p><strong>Main Verifiable Outcomes:<\/strong> Registration and editing UI\/API, extraction and validation flow, and initial demonstration<\/p><\/div><div class=\"mw-time\"><h3>January-March 2027<\/h3><p><strong>Core Work:<\/strong> Related-case retrieval, event-log generation, basic process discovery, ConceptMiner and Concept Index integration, and MCP server\/API access<\/p><p><strong>Main Verifiable Outcomes:<\/strong> Knowledge and episode retrieval, process visualization, and AI-agent access demonstration<\/p><\/div><div class=\"mw-time\"><h3>April-June 2027<\/h3><p><strong>Core Work:<\/strong> Single Wiki Builder integration; generation of operational documents, process descriptions, and case collections; participant evaluation scenarios<\/p><p><strong>Main Verifiable Outcomes:<\/strong> Integrated demonstration of knowledge, concepts, episodes, and processes<\/p><\/div><div class=\"mw-time\"><h3>July-September 2027<\/h3><p><strong>Core Work:<\/strong> Incorporation of evaluation results, refinement of permissions and change history, documentation, samples, final tagged release, and outcome report<\/p><p><strong>Main Verifiable Outcomes:<\/strong> Reference implementation, technical materials, evaluation results, and final symposium<\/p><\/div><\/div><div class=\"mw-note\">Detailed timing, feature priorities, and delivery methods will be adjusted according to technical validation and common value for participating companies.<\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"program\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">14<\/div><h2 class=\"mw-section__title\">Year-Round Online Program<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-program\"><div class=\"mw-program__row mw-program__head\"><div>Format<\/div><div>Program Content<\/div><div>Value to Participants<\/div><\/div><div class=\"mw-program__row\"><div class=\"mw-program__label\">Monthly Sessions<\/div><div>Development progress, technical demonstrations, design decisions, and Q&amp;A<\/div><div>Share the development process and design rationale, not only the completed system<\/div><\/div><div class=\"mw-program__row\"><div class=\"mw-program__label\">Use-Case Review<\/div><div>Examine common operational information, evaluation methods, and implementation barriers across participants<\/div><div>Reflect practical requirements in common specifications without disclosing company-specific information<\/div><\/div><div class=\"mw-program__row\"><div class=\"mw-program__label\">Thematic Lectures and Reviews<\/div><div>Lectures and reviews by relevant researchers, technical specialists, and practitioners<\/div><div>Validate the work from both research and practical perspectives<\/div><\/div><div class=\"mw-program__row\"><div class=\"mw-program__label\">Materials Archive<\/div><div>Recordings, technical materials, evaluation procedures, and update history<\/div><div>Support internal sharing and ongoing evaluation<\/div><\/div><div class=\"mw-program__row\"><div class=\"mw-program__label\">Final Report and Symposium<\/div><div>Reference implementation, architecture, known limitations, evaluation results, and future roadmap<\/div><div>Support decisions on internal adoption, additional proofs of concept, and participation in a future phase<\/div><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"participation\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">15<\/div><h2 class=\"mw-section__title\">Participation Terms and Project Positioning<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-participation\"><div class=\"mw-price\"><small>Participation Fee, Excluding Tax<\/small><strong>JPY 2.5M<\/strong><p>Up to two designated participants per unit<\/p><p>Multiple units permitted<\/p><\/div><div class=\"mw-participation-list\"><div class=\"mw-participation-row\"><h3>Payment Terms<\/h3><p>50% upon application and contract execution; the remaining 50% before the project begins.<\/p><\/div><div class=\"mw-participation-row\"><h3>No Minimum Launch Threshold<\/h3><p>The project will not be canceled and fees will not be refunded solely because participation does not reach the expansion target. Contracted core outcomes will still be delivered.<\/p><\/div><div class=\"mw-participation-row\"><h3>Participant Confidentiality<\/h3><p>Company names, logos, and participant names will remain confidential in principle. Prior consent will be obtained before disclosure.<\/p><\/div><div class=\"mw-participation-row\"><h3>Intellectual Property and Governance<\/h3><p>Participation does not confer ownership interests in intellectual property, voting rights, exclusive rights, or authority over the product roadmap.<\/p><\/div><div class=\"mw-participation-row\"><h3>Permitted Use<\/h3><p>Deliverables may be used for internal evaluation and research within the contractual scope. Redistribution and use in competing services will be prohibited.<\/p><\/div><div class=\"mw-participation-row\"><h3>Company-Specific Work<\/h3><p>Company-specific proofs of concept, integrations, data preparation, customization, and production deployment support will require separate agreements.<\/p><\/div><\/div><\/div><div class=\"mw-positioning\"><strong>Positioning of This Project<\/strong>This is an early-participation, multi-client development program in which advance participation by multiple companies makes a common enterprise AI foundation possible. It is not a donation, an equity investment, or joint research based on shared intellectual-property ownership. It is a B2B development service providing defined deliverables, usage rights, and access to the development program.<\/div><\/div><\/div><\/section>\n<section class=\"mw-section mw-section--soft\" id=\"research\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">16<\/div><h2 class=\"mw-section__title\">Research Foundations and Primary Reference Candidates<\/h2><\/div><div class=\"mw-body\"><p class=\"mw-lead\">The project does not promise to reproduce each theory faithfully or implement all of them during Phase 1. These are design references for translation into reference implementations that can be evaluated in enterprise environments.<\/p><div class=\"mw-research\"><div class=\"mw-research-row\"><div class=\"n\">01<\/div><div><h3>LLM Wiki<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">Andrej Karpathy<\/p><\/div><div><p>Compile source material into reusable, cross-referenced knowledge pages rather than searching raw fragments directly.<\/p><\/div><\/div><div class=\"mw-research-row\"><div class=\"n\">02<\/div><div><h3>Process Mining<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">Wil M. P. van der Aalst and others<\/p><\/div><div><p>Discover actual business processes from event logs and analyze deviations, bottlenecks, repetitions, and exceptions.<\/p><\/div><\/div><div class=\"mw-research-row\"><div class=\"n\">03<\/div><div><h3>Generative Agents<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">Joon Sung Park and others<\/p><\/div><div><p>Store experience as natural-language memory, retrieve it by relevance, recency, and importance, and use it for reflection and planning.<\/p><\/div><\/div><div class=\"mw-research-row\"><div class=\"n\">04<\/div><div><h3>Complementary Learning Systems<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">McClelland, McNaughton, and O\u2019Reilly<\/p><\/div><div><p>Link rapid recording of new events with slower formation of general structures from accumulated experience.<\/p><\/div><\/div><div class=\"mw-research-row\"><div class=\"n\">05<\/div><div><h3>Case-Based Reasoning<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">Aamodt and Plaza<\/p><\/div><div><p>Retrieve, reuse, revise, and retain past cases as a continuing problem-solving cycle.<\/p><\/div><\/div><div class=\"mw-research-row\"><div class=\"n\">06<\/div><div><h3>KDD \/ Knowledge Discovery<\/h3><p style=\"font-size:.82rem;margin-top:.35rem\">Fayyad, Piatetsky-Shapiro, Smyth, and others<\/p><\/div><div><p>Critically extend the KDD process by converting analytical outputs into documents, processes, and cases usable by business personnel.<\/p><\/div><\/div><\/div><div class=\"mw-additional\"><span>Hierarchical Memory \/ MemGPT<\/span><span>Global Workspace<\/span><span>Soar \/ ACT-R<\/span><span>Tolman-Eichenbaum Machine<\/span><span>Active Inference<\/span><\/div><\/div><\/div><\/section>\n<section class=\"mw-section\" id=\"leader\"><div class=\"mw-wrap\"><div class=\"mw-section__head\"><div class=\"mw-section__num\">17<\/div><h2 class=\"mw-section__title\">Project Director<\/h2><\/div><div class=\"mw-body\"><div class=\"mw-leader\"><div class=\"mw-leader__name\"><small>President and Principal Researcher, Mindware Research Institute, Inc.<\/small><strong>Kunihiro Tada<\/strong><\/div><div><p class=\"mw-leader__bio\">Beginning in 1982, he was involved in planning and operating technical seminars on advanced technologies, including new media, at a publishing and seminar company. From 1985, he conducted business-opportunity research in advanced technology fields at a major consulting company. In 1986, he organized an AI Chip Seminar that included fuzzy inference chips. In 1997, he wrote a serialized article on Concept Research for a management magazine. In 1998, he began research focused on Kohonen&#8217;s Self-Organizing Map. From 2000, he served as the Japanese distributor for Viscovery SOMine and also handled HUGIN and XLSTAT. Following XLSTAT&#8217;s acquisition in 2023, he began developing proprietary systems and established the core ConceptMiner technology using Growing Neural Gas and a Minimum Spanning Tree.<\/p><div class=\"mw-advisor-note\">Relevant researchers, technical specialists, and practitioners will be invited for thematic lectures and reviews.<\/div><\/div><\/div><\/div><\/div><\/section>\n<section class=\"mw-cta\" id=\"contact\"><div class=\"mw-wrap\"><h2>Request the Phase 1 Information Package and Implementation Demo<\/h2><p>Detailed schedules, contractual terms, advisors, and final usage conditions for the deliverables will be confirmed after formal approval. Inquiries regarding participation, briefings, and implementation demonstrations are welcome.<\/p><div class=\"mw-actions\"><a class=\"mw-btn mw-btn--primary\" href=\"https:\/\/www.mindware-jp.com\/en\/contact-2\/\">Contact<\/a><a class=\"mw-btn mw-btn--secondary\" href=\"#top\">Back to Top<\/a><\/div><\/div><\/section>\n<\/main><footer class=\"mw-footer\"><div class=\"mw-wrap mw-footer__inner\"><div><strong>Mindware Research Institute, Inc.<\/strong><br>Mindware Multi-Client Development Project<\/div><div>Phase 1: October 1, 2026 &#8211; September 30, 2027<\/div><\/div><\/footer><\/div><script>\n(function(){\n  const root=document.querySelector('.mw-site-owm');\n  if(!root)return;\n  const menu=root.querySelector('.mw-menu');\n  const nav=root.querySelector('#mw-nav');\n  if(menu&&nav){\n    menu.addEventListener('click',()=>{const open=nav.classList.toggle('is-open');menu.setAttribute('aria-expanded',String(open));});\n    nav.querySelectorAll('a').forEach(a=>a.addEventListener('click',()=>{nav.classList.remove('is-open');menu.setAttribute('aria-expanded','false');}));\n  }\n})();\n<\/script>\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n<div class=\"wp-block-group featured-post-pattern\" style=\"padding-top:var(--wp--preset--spacing--medium);padding-bottom:var(--wp--preset--spacing--medium)\"><div class=\"wp-block-group__inner-container is-layout-constrained wp-block-group-is-layout-constrained\">\n\n\n<div style=\"height:8px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n\n\n\n\n\n<div style=\"height:32px\" aria-hidden=\"true\" class=\"wp-block-spacer\"><\/div>\n<\/div><\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mindware Multi-Client Development Project | Building a Self-Organizing Operational World Model Mindware Projec&#8230;<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_kad_post_transparent":"disable","_kad_post_title":"hide","_kad_post_layout":"fullwidth","_kad_post_sidebar_id":"","_kad_post_content_style":"unboxed","_kad_post_vertical_padding":"default","_kad_post_feature":"default","_kad_post_feature_position":"","_kad_post_header":false,"_kad_post_footer":false,"_kad_post_classname":"","footnotes":""},"class_list":["post-7","page","type-page","status-publish","hentry"],"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/pages\/7","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/comments?post=7"}],"version-history":[{"count":52,"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/pages\/7\/revisions"}],"predecessor-version":[{"id":419,"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/pages\/7\/revisions\/419"}],"wp:attachment":[{"href":"https:\/\/www.mindware.llc\/wp-json\/wp\/v2\/media?parent=7"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}