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  • Introduction
    • Machine-to-Machine Learning White Paper Introduction
    • What is M2ML?
    • 3 Waves - Overcoming Limitations of Human Performance
  • Wave 1
    • Wave 1 – Vision & Identification
    • Wave 1 – Archetypes
    • Wave 1 – Opportunity Areas
      • Automating & Roboticizing Stodgy Industries
      • Accelerating Serendipitous Discovery
  • Wave 2
    • Wave 2 – Building an MVP
    • Wave 2 – Archetypes
    • Wave 2 – Opportunity Areas
      • Automating & Roboticizing Stodgy Industries
      • Accelerating Serendipitous Discovery
    • Wave 2 - The North Star: Building for the J-Curve
  • Wave 3
    • Wave 3 – Building a Platform
    • Wave 3 – Archetypes
    • Wave 3 – Opportunity Areas
      • Automating & Roboticizing Stodgy Industries
      • Accelerating Serendipitous Discovery
  • Insights
    • Identifying Winners Across Waves
    • Case Study: Rapid Robotics
    • Go-to-Market Playbook
      • Product
      • Sales
      • Platform
    • Waves in Motion
  • Conclusion
    • Why Now?
    • Get in Touch
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  • Software-Powered Retrofits to Build New Smart Workflows
  • Human Augmentation to Execute and Scale Analog Processes with Machine Strength
  • Going Big with Automating High Frequency Tasks
  • Designing New Paradigms, Supply Chains and Open Networks for Moving Goods
  1. Wave 3
  2. Wave 3 – Opportunity Areas

Automating & Roboticizing Stodgy Industries

Optimizing service-heavy processes

Software-Powered Retrofits to Build New Smart Workflows

​Software-powered retrofits, shifting costs from hardware to software, are easy solutions to retain and expand by avoiding the CapEx and time of a ground-up solution.

  • Built Robotics​ is a prime example – a ​hydraulics retrofit makes heavy earth-moving equipment both autonomous and affordable.

Interoperability between devices that use a multitude of protocols makes connectivity a challenge – software powered retrofitting is the inevitable answer​.

  • Companies like ​Zinier​, Tulip​, ​and Parsable​​ retrofit prevalent operator-run devices to become intelligent and avoid human procedural errors.

Human Augmentation to Execute and Scale Analog Processes with Machine Strength

​The enterprise benefits from instant feedback & support via interfaces that harmonize human computer interaction. The result is an improvement of working conditions alongside output.

  • Dusty Robotics produces a BIM-driven robotic layout that is as precise in the physical world as it is digitally, and Drishti offers visual QA in manual assembly lines leading to quality, productivity, and training improvements.

Going Big with Automating High Frequency Tasks

The generalization of hardware to a range of tasks is a hard problem​ to solve, while low-hanging fruit exists in the majority of repetitive tasks requiring only a crab-claw level of accuracy.

  • Companies focused on: welding (Path Robotics), recycling conveyor systems (AMP Robotics), and supply delivery in hospitals (Diligent Robotics) have proven ROI by focusing on tasks that weave into larger systems, ultimately unlocking massive markets (see Rapid Robotics Case Study here).

Designing New Paradigms, Supply Chains and Open Networks for Moving Goods

To create step-change efficiencies, sometimes founders must go beyond a single task and focus on bold process design improvements across an entire ecosystem.

  • Examples include modular prefabricated housing (Periscope Homes is optimizing the entire housing supply chain), modular loading and unloading of trucks (Slip Robotics is creating 25x more efficient load times), software-powered cross-docking (a la Bee portfolio company Warp Logistics), and dynamic optimization to manage truck load delivery time (Baton is cutting trucking "detention" wait times by 50%).

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Last updated 1 year ago

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