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Nanosense engr 245 lean launchpad stanford 2019

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business model, customer development, e245, engr245, lean launchpad, lean startup, stanford, startup, steve blank

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Nanosense engr 245 lean launchpad stanford 2019

  1. Smart Monitoring at the Edge nanoSense Chris Young Daniel Villamizar Roy Nicolet Sophia Shramko Mindy Chang Hacker PhD, EE Designer PhD, EE Hustler/Picker MBA1, Bsc.EE Picker MBA2, Bsc. EE Hustler MBA1 Radhika Malpani Rekha Pai Mentors Interviews: 87 AI Hardware at the Edge
  2. Introduction Video
  3. What is nanoSense? Where Did We Start? low-power edge-processing low data-rate built-in privacy microphone camera Smart Sensors AWESOME
  4. What is nanoSense? Where Did We Start? wake-up microphone camera Smart Sensors
  5. Smart Home Speaker
  6. nanoSense as a smart wake-up Smart Home Speaker
  7. • Semiconductor companies • Emerging system companies (e.g. Oculus, Roomba, Nest, Anki) • Complimentary IoT sub-components (NB- IoT, MEMS, emerging sensors, etc.) • Early institutional adopters (DARPA) • Early-adopting product giants (Apple, Google, etc.) ● Consumer technology giants with in-house chip design ● Automated warehouse. ● Emerging systems, application-specific, wearables ● Semiconductor industry ● Chip design IP enabling front-end compression for smart consumer systems. ● Packaged sensor modules with interface API to extend capabilities of industrial/manufacturing equipment. ● Smart sensing previously unachievable at the edge for wearable devices enabled by our low-power solution. ● Performance improvement and additional feature to interface with their existing backend processing. • High R&D cost: Engineering salaries; tools; silicon prototyping • High manufacturing cost (stand-alone channel) • Design cycle time ~18 months • Sales from stand-alone catalogue product (across all customer segments) • Turnkey custom solution and ongoing support for aggressive performance AV ML systems • IP licensing (large volume customers segments) • (Re)define market segment based on MVP performance • Determine specification requirements according to customer preferences • Create support system within targeted applications to win and keep customers • Sub-component supplier __ __ • Licensing model for current IP __ __ • Support for integration and product shipping to enable adoption • Targeted proof of concept(s) • Engineering design tools (CAD) • Human resources- engineers, product managers, marketing, sales, BizDev. • IP license. __ __ • Chips/modules with API included to interface to arbitrary backend processors. __ __
  8. Value Propositions ● Power ● Bandwidth ● Latency ● Memory Customer Segments ● Electronic system manufacturers ● Smart warehouses ● Chip Manufacturers
  9. Search for The Killer Segment “Think broadly...” - Steve Blank | office hour Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Smart Cities Consumer Industrial Commercial Autonomous Vehicles
  10. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Smart Cities Autonomous Vehicles ResellerDistr.$ SGA R&D COGS - % $ SGA R&D Tools Manufacturing - %
  11. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Smart Cities Autonomous Vehicles
  12. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Smart Cities Autonomous Vehicles
  13. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Smart Cities Autonomous Vehicles Full-stack → Value
  14. ● Getting meaningful interviews for our market is hard ● Constant debate: where should we focus? ● Engineering from Mars, business from Venus ● Mismatch in expectations Crisis #1: Team Dynamics
  15. ● Team dynamics is very important ● Set clear expectations from all sides ● Admit mistakes quickly and move on ● Let people do what they are good at doing Learning: Cross-Functional Team
  16. Crisis #2: Value-Add “For hardware startups, typically, the value-add has to hit you like a hammer to the face ” - George John | In-class presentation feedback ● No “killer app” for our technology ● Too much competition and substitutes ● Semiconductor business needs high revenue models
  17. The assumed value proposition Smart Home Speaker
  18. Where is the real value? Smart Home Speaker
  19. Learning: Get Stay Outside The Building Value Propositions ● Sensing that was previously impractical or impossible ● Stack-rich solution ● High value-add ● Stay the course. Unnecessary to expect a killer app in 5 weeks ● So far we were looking for markets where: keep the product simple
  20. Hammer #1: Johnson Controls “Can your audio solution detect the sound of leaking water?” - Robert Locke | Mentor & Biz Dev - Johnson Controls ❏ Enabled by us ❏ Full-stack ❏ Simple ❏ Value-add Other Similar Potential Applications ● Building occupancy ● Alarm broadcasting (from existing local sensor) ● Motor anomaly monitoring
  21. Hammer #2: Conference
  22. Hammer #2: Conference “If all we did was sell steam trap monitoring we could run a healthy business” - Ben Calhoun | CTO, PsiKick
  23. The value is not in the chips, but in the data they collect. We Live in a Progressively Data Driven World
  24. MVP Iteration
  25. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Surveillance Smart Homes Buildings Smart Cities Consumer Industrial Commercial Autonomous Vehicles ❏ Enabled by us ❏ Full-stack ❏ Simple ❏ Value-add
  26. Search for The Killer Segment Wearables Smartphone Drones Medical Devices Consumer Industrial Commercial Autonomous Vehicles Monitoring as a Service
  27. MODULE SMART SENSOR POWER RADIO EASY INSTALLATION & LOW MAINTENANCE ALWAYS-ON DATA COLLECTION REAL-TIME DECISIONS ANALYTICS The Enabler Can the Real nanoSense Please Stand Up?!
  28. UPDATED - Get, Keep, and Grow Customers KEEP GROWGET Target - Largest number of insurance claims. - Devices with high cost of failure. Keep - Subscription based monitoring. Next-Sell - Same hardware, new analytics - fast to change software! - Iterate on hardware - board level to chip level implementations.
  29. “Providers are looking for enhanced data collection. There is a move from analytics to real-time decisions at the edge.” - Cindy Maike | GM Insurance - Cloudera “There are 50 million steam traps in the United States” - Sean Mankhen | Senior Engineer - PsiKick Smart Monitoring Value Propositions ● Real-time, always-on loss- prevention and analytics for building managers and insurtech providers. ● Smart monitoring for failure detection, analysis, and prevention. ● New sources of data collection for analytics in challenging environments. “Can you tell me which houses are most at risk for water damage?” - Chris Knievel | Strategy Dev. - CSAA Insur.
  30. ● Early institutional adopters (DARPA) ● Insurance providers ● Asset Managers ● Data Analytics (the backhole for all the data - C3IOT, Cloudera) ● Complimentary IoT sub-components (NB- IoT, BLE, MEMS, emerging sensors, etc.) • High R&D cost: Engineering salaries; tools; silicon prototyping • High manufacturing cost (stand-alone channel) • Design cycle time ~18 months • Sales from stand-alone turnkey product (across all customer segments) • Direct sales to insurance companies, asset managers and industrial facilities/machinery. • Subscription for monitoring, hardware updates. • Find early adopters. • Determine specification requirements according to customer preferences • Create support system within targeted applications to win and keep customers • Targeted proof of concept(s) • Engineering design tools (CAD) • Human resources- engineers, product managers, marketing, sales, BizDev. ● Sub-component supplier ● Software/Firmware and integration support to make a adoption seamless ● Provide smart sensing solution including data analytics that is compatible with current infrastructure. ● Real-time, always-on loss-prevention and analytics for insurtech providers. ● Smart monitoring for failure detection, analysis and prevention. ● Data collection in constrained environments. ● Direct Sales to Insurance companies, asset managers, and industrial facilities/machinery. ● Industrial IoT players ● Insurance companies ● Asset Managers
  31. Chris Young Daniel Villamizar Roy Nicolet Sophia Shramko Mindy Chang Hacker PhD, EE Designer PhD, EE Hustler/Picker MBA1, Bsc.EE Picker MBA2, Bsc. EE Hustler MBA1 Radhika Malpani Rekha Pai Where We Go from Here Mentors
  32. Thank You! Questions?

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