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Evolving a data supply chain and disrupting the Google model of ignoring data ownership and the Facebook model of co-opting data ownership. The data supply chain model assumes the person or the owner of the device that creates data is the owner of that data and should have the right to trade in in an open marketplace.


  • 1.Presentation to Investors December 2011

2. Unlocking Value in Data The future belongs to the companies and people that turn data into productsOReilly Radar Report1. Mission2. Executive Summary3. Knowledgelevers4. Data Exchange5. The Data Federation and Exchange Space6. Job To Be Done7. Knowledgelevers Tool Sets8. IP Protection for Knowledge Levers and Derivative Applications I9. IP Protection for Knowledge Levers and Derivative Applications II10. Upside Potential11. Differentiators12. Staging Our Income Pyramid13. Facilitating Data Trading14. Traders Need Tools15. Tools and Development Progress16. Strengths - Needs - Risks17. Our Founder18. Evolving The Team19. Exit Strategy20. Bottom Line and SummaryAppendix 3. MissionDisrupt enterprise data products through just in timenotifications for CRM, Supply Chains, and Business Intelligence.Data is the oil of the 21st century Copyright 2011 Compages 4. Executive SummaryUnlocking value in data through enabling a new market a hybridbetween what did for used goods,did for retailersand for the music industry.We will implement and protect methods and systems to collect feesfor enabling data to be traded and operated upon in real time. A multi-billion dollar opportunity 3.5 Million invested into software and IPConcept and technology validated by currently working installationsRobust IP with supportive prototypingCopyright 2011 for Knowledgelevers.com1 5. Experienced in data managementDeep understanding of problems faced by researchers and risk managersProjected valuation takes us to $500 million in 2016Multiple sales and growth channels Broad market Diverse market for buyers of data. Diverse producers of datawho want to sell it. Effort to identify which data to buy or sell.Need for actionable intelligence for risk assessment and competitive advantage ResistanceOpportunityCopyright 2011 for 2 6. Data ExchangeData Federators and DistributorsData Accumulators and AggregatorsCritical Research Enterprises - Cut losses Gallup, Gartner Distribute the right data from useless research and liabilities from to customers missed indicators. A Market in Searchof a Trading PlatformData Based Risk MitigatorsData Creators and ProducersStock Fund Managers or Homeland SecurityAll businesses, especially retailers and Notify the right person as the dots get financial institutions Sell fallow data to connected.buyers.Copyright 2011 for 3 7. The Data Federation and Exchange Space Node51 WarehousingVisualization DataCloud Apps,BusinessConsultingOdd Fellowsand Linking for andTransformation Appliances,Intelligence Analytics,Specialized Computation ManagementSuites Extraction,Data Exchange and Storage CollaborationCustomers orJoint Venture Channel ChannelOEM OutletsSales OutletsJoint SalesPotentialPartners Partners Partners orCompetitors Competitors Nobody in the space has monetized automated chains of data or triggered actions.Copyright 2011 Knowledgelevers.com4 8. Job To Be DoneBe the global leader for brokering actionable data in real time. Problem SolutionData exchange is constricted due toSoftware and infrastructure toNo effective marketplace for offering or discovering dataPost/offer and discover data to a central locationNo easy way to buy or sell Establish standardized data exchange PRICING agreementsNo easy way to determine a price Provide a mechanisms for supply-side or demand-side pricingMultiple data formatsCollect and federate data in real time or bypass federationNo standardized data updates Enable updating and event triggeringNo standardized tools for triggering actions based on data Provide a self-service interface for simple data sharing Every Internet User - a Data TraderEvery Business - a Data Vendor or Consumer Every Employee or Researcher a Data Creator 5 9. Knowledgelevers Tool Sets Connection Tools RiskCommunicationCalculation ReductionToolsTools and CRMCombination ToolsCopyright 2011 6 10. IP Protection forKnowledge Levers and Derivative Applications IBig Picture: Patent methods and systems involving pricing and feesassociated with data trading.Protect prices and fees for Gateways to Datasets1. Transmission from electronic devices like Smart Phones that offer GPS locations and point of sale transactions2. Enrollment into data trading venues through data strings like Matrix Codes, RFID tags, and direct to web services connections3. Transmission to or from social networking sites like Facebook and Twitter in the event the Supreme Court determines ownership to be by the producer of the data or the owner of the device originating the dataProtect prices and fees for Improvement of Datasets1. Iterative additions to a dataset2. Alternate versions of a dataset3. Immediate utility of the data format (Data Item Pair) Copyright 2011 7 11. IP Protection for Knowledge Levers and Derivative Applications IIProtect prices and fees for Interaction with Datasets1. Setting up triggers to initiate server actions upon changes in a dataset2. Tracking interaction with a GUI associated with a dataset3. Linking enrollees (contributors) to data protocols and associated datasets4. Linking recipients of reports or server actions to data protocols and associated datasetsProtect prices and fees for assigning Value to a Data Item1. Popularity of the item2. Reputation of the source for the data3. Importance of the item relative to other data itemsProtect prices and fees for Financial Transactions Involving Data1. Uploading data to a parent dataset2. Use of validation keys to connect contributors with financial institutions3. Enrollment of a new contributor or recipient into a data supply chainCopyright 2011 Knowledgelevers.com8 12. Upside PotentialAs data strings or matrix codes are used for rapidenrollment into social media sitesAs data strings or matrix codes are expanded intoenrollment of consumers for feedback and riskmanagementIf ownership of data generated upon or within anelectronic device resides with the owner of the deviceIf user expectations shift from analytics or statistics toactionable intelligence Copyright 2011 Knowledgelevers.com9 13. DifferentiatorsWe understand and can match our competitors capability and technology, but we are thefirst transactional and actionable data firm hence our name Knowledgelevers. Competitors KnowledgeleversDatabases Big data Data Items Small dataData Federation and AggregationData Chains, Streams, CombinationsData Transformation and Analysis Data Assessment for Actionable ValueData MiningData Triggering and NotificationsData Storage and Warehousing Forward and Backward RedistributionSoftware Sales and Consulting Income Transactional IncomeIT Departments - Centralized ManagementLocal End Users - Distributed (Individual Users)Siloed by Organization or Function Socially NetworkedScheduledReal-timeValue Proposition is Organized DataValue Proposition is Actionable InformationCopyright 2011 Knowledgelevers.com10 14. Staging Our Income Pyramid 10 Million Users for 200 Billion Data PointsStage 5 SaaS $.01 per field/3% transaction Continuous incomeData Market 100,000 BuyersStage 4SOFTWARE -Direct toResearchers & $80,000 per saleVC Capital Enterprise Risk 15% MaintenanceManagers Continuous Income Stage 3 3,000 Licensees Skip if VC OEM LICENSES - for Data Distribution Businesses$50,000 per license capitalStage 2 500,000 BuyersSHAREWARE - Self-service Consumers - to set upSkip if exchanges, wrangle data, trigger actions and notifications$99 eachVC capital 125,000 BuyersStage 1CURRENT CUSTOMERS - Expanded sales of upgraded Employee$25,000 per saleBeta testingPerformance and Risk Management Software to the public sector andand validation hospitals.15% Maintenance Continuous Income Year 5 = Exit at Year 1Year 2Year 3 Year 4 $500,000,000 to$268,000 $4,000,000$32,000,000$246,000,000$800,000,000 Copyright 2011 11 15. Facilitating Data TradingAccess to multiple data types and owners:Tables, spreadsheets, and distributed databasesAbility to drill down or roll up for federation or subsets:Aggregating by the data item, the data item pair, the data stream, or the dataset.Ease collecting from multiple devices, messaging services, observers, and consumers:Track changes, create and audit dataFlexibility in MONETIZING AND SETTING VALUE:Rarity, reputability, integrity, usability, compatibility, popularity, recency, format friendlyStreaming:Ongoing real-time or scheduled data updatesSetting THRESHOLDS AND TRIGGERS FOR ACTIONS:Notification and/or other automated actions based on schedule and/or new or changed data Copyright 2011 for 12 16. Traders Need ToolsImplement a data marketplace to automate uploading and downloading,pricing, payment, and action upon data in real time. User friendly and secure applications to monetize dataUniversally post and exchange data Security and authentication for data transportEasily input pricing variables to enable fair compensation or reciprocity for data Price per question ContributorSpecific utilityand answer pairPrice per fieldPopularity rating (rarity/recency/Automated actionsreputation ratingcompatibility)Enable fees and charges for exchange and payment processDevice uploads and downloadsPayment and transaction toolsMembership fees, activation fees, convenience fees, subscription fees, volume discounts .Data is most valuable as and when it changes. Copyright 2011 for 13 17. Tools and Development Progress20122010Prepare for GrowthExpand PatentProtection Complete Prototypes2009 Fold Legacy Applications Monetize Weightingtogether with PrototypesArchitect Prototype Monetize Handshakes Up-sell current customers Recruit Developers Monetize Popularity and Secure Venture Capital/Partners Fold in Legacy Software Recency Expand Management Team Confirm Customer Need Monetize GUI2006 Further Design and Protect Establish Coding and Design Embed Systems, Tools, andPatent Ap