Some example projects that could be built using Level 3:

• Attention management: email, social media, texting, collaboration, advertising – a system that will manage these based on user attention desires.
• Automated invention: come up with invention ideas using an automated system.
• Capital expenditure allocation: build an application to identify where capital need to be expended, which areas, which technologies, which capabilities are needed.
• Compassion profiling: find where each employee belongs in an organization based on talent, skill, and attitude.
• Complex dynamic line of business transaction management: build information model(s) to cover the various workflows that a business may need to use in the future and use the models to control all workflow in an application.
• Complex inventory flow management: build information model(s) to cover the various states that a piece of inventory could be in.
• Complex page level security management: build an information model and use it on each page, for each data ‘section’, for each user/customer, and for each resource/function.
• Data finder / deep web search engine: build a web search engine based on information models. Select as a niche, sites that cover statistical information, databases, large text files, data files, the deep web etc.
• Extract legacy application value for migration: extract information from a legacy application for use in developing replacement apps. Build information models embedded in the logic of the legacy application.
• Fill holes in a team talent set: identifying gaps in a team’s talent set by identifying each member’s talent, skill, and attitude and using this to prioritize task assignments, and using this to identify what is missing for hiring purposes, and identifying how well each candidate fills those gaps.
• Finding the right talent: build an application for hiring – identify talent through word-level resume analysis, blog analysis, social media analysis, forum postings. Build a dictionary of word to talent translations.
• Global niche economics: project collaboration, attention management, information model collaboration, cloud existence, production, design, distribution, customer involvement, parts and software, micro-finance, attention scoping.
• Glomming database types: database model simplification, type concentration, type centralization, to get the biggest bang for the buck, identify the core complex states.
• HL7 Auto-version: Build an application that can work with any version of HL7 without having to do much application rework.
• Hyper-science: build an application to convert scientific concepts into information form, then use this to do attention management with the scientific community.
• Implicit geometry: a technology to compete with and collaborate with polygons, fuzzy information for content, recognition for interactions, generators for display, models for shaping.
• Individualized marketing documents: generating individually targeted marketing documentation based on 1)customer input, 2)customer search patterns, 3)customer purchasing patterns.
• Internal organization information finder: Characterize each document in an organization using information model(s). Use these to find information, coalesce information, find information gaps.
• Knowledge based CMS: build a CMS system which provides metadata as part of its knowledge base.
• Mergers and acquisitions: what functionality is duplicated and what functionality needs to be or can be extracted for use.
• Simplify AI: Simplify AI heuristics through recognition of fuzzy states.
• Software capability inventory: identifying which software capabilities you already have and which you need.
• User aligned data entry: Build user interfaces that can handle 0nf entries.
• Using the results of data mining: Scrape the results of BI, data mining, and data analytics into an active information models. Then use them to power applications.
• Venture capital allocation: which projects deserve more support and which less.