Launchpad
MicroAI Launchpad is an enterprise platform for development of end-to-end, AI-enabled, asset management ecosystems. Launchpad provides next-generation capabilities in AI-program development and deployment, workflow automation, data ingestion, and data visualization.
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Rapid AI Program Development
MicroAI Launchpad is a Kubernetes-based platform that delivers AI-enabled enterprise asset management (EAM), asset performance management (APM), intelligent workflows, analytics, and visualization. The platform provides rapid development, testing, and deployment of fully customized AI/ML capabilities: Developer advantages include:
MicroAI Launchpad shortens development time, reduces costs, and provides a quicker time to market.
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Easy Library Access
Developers can quickly access and onboard MicroAI’s AI and ML software libraries. No more having to conduct time-consuming searches for SDKs that may or may not meet their requirements.
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Leverage Endpoint AI
Simplified system development that leverages MCUs and MPUs that have been embedded with MicroAI™ Edge-native software. Removes much of the time, complexity, and cost from system development.
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Live Testing and Iteration
Developers can easily test their initial designs within a controlled, real-time, environment. Design iterations can be quickly implemented and validated.
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Seamless Integration
Launchpad removes the complexity of integrating with other ecosystem components. Integration can be processed and validated within the Launchpad platform.
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Complete System Testing and Launch
Birds-eye-view testing of the entire Edge-AI ecosystem in preparation for deployment. Eliminates the problem of siloed testing and visibility limitations.
End-to-End Data Pipeline
MicroAI’s Enterprise Grade Platform Consolidates All Components Needed for Deploying AI-Power Solutions on Devices/Machines and on-premise
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Embedded AI
AI Signal Processing for Endpoint/Edge Gateway Based Agent Support
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Connectivity
Agnostic to Protocol WIFI, 5G, LTE, CAT-M, NB-IoT, LoRa, etc.
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Hyperconverged Platform
Workflows, Activation, Billing, Smart Connectivity, Data Management & Auto-Scaling Environments
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AI Driven Insight
Industry Specific KPIs/Analytics, PdM, and AI Driven Dashboards
EAM and APM Operational Excellence
Machine and process-intensive operations need a solution that combines the enablement and training of asset-centric AI/ML algorithms, the application of AI to create intelligent workflows, and the ability to quickly synthesize and visualize data—all within a secure environment. Launchpad bridges existing intelligence gaps by providing:
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Data Ingestion
Seamless and secure ingestion of data from a wide variety of industrial, manufacturing, and automotive devices and equipment. This can include sensors, robots, inspection machines, PLC’s, IoT field assets, and databases.
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Asset-Centric Scalability
Unlike other methodologies, Launchpad can be deployed on multiple smart assets, individually and simultaneously, to enable asset-specific performance benchmarking, real-time data visualization, intelligent field service workflows, and more.
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Embedded Security
Smart asset performance monitoring that includes AI-enabled security and SSL protocols. Protection from cyber-threats using cutting-edge AI capable encryption methods that protect against Zero-Day cyber-attack and other malware intrusions.
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Intelligent Workflows
The embedding and training of intelligent workflows that are dynamic, automated, and locally managed. Edge-AI workflows that learn and self-adjust to keep processes finely tuned for maximum efficiency.
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Visualization and Dashboarding
A powerful—centralized–visualization engine that enables real-time event management across individual assets within a smart asset ecosystem. Drag and drop, customizable, dashboards can be configured to visualize real-time asset data and to trigger actionable alerts.
Impact to Operational KPI
Unlike other solutions that focus on a narrow range of operational functions, Launchpad provides enhanced intelligence, visibility, and control across a broad cross-section of mission-critical Key Performance Indicators (KPI). Tangible improvements are realized within the following areas:
Asset Management
- Remote monitoring of individual assets within an asset ecosystem
- Rapid asset performance anomaly detection and response
- Customizable drag-and-drop asset monitoring dashboards
- AI-enabled, machine-specific, predictive maintenance routines
- Improved machine throughput and uptime rates
- Localized protection of devices and machines from Zero-Day cyber-attack
- Extended lifespan of expensive assets
- Lower cost of asset ownership
Business Workflow Optimization
- Next-generation sales process management
- Automation of contract generation and management processes
- AI-enabled dispatch scheduling and maintenance technician management
- Self-learning invoice management optimization
- Embedded AI algorithms for management of alerts and responses
The Problem
Developers are often tasked with fulfillment of AI initiatives within time frames that have been compressed due to business and/or operational imperatives. These challenges are exacerbated by the lack of a comprehensive, developer-friendly, platform that provides all necessary elements to design, test, integrate, and launch an AI initiative.
Typical challenges for the developer community and key business stakeholders would include:
- Too much time is spent searching for AI and ML libraries that meet the requirements of specific APM and EAM ecosystems.
- SDK uploading/onboarding process is often cumbersome and error prone.
- Limited ability to test and iterate designs within a self-contained, real-time, environment.
- Cumbersome integration with external system components negatively effects ecosystem integrity.
- All the above add time, complexity, cost and risk to the design and deployment process.
- Difficult to estimate program costs and maintain budgetary control.
- The piecemeal design approach inhibits a consolidated managerial view of program status.
- Program delays resulting from having to work within too many disconnected tools and applications.
- Lack of ability to integrate business transaction workflows that are self-learning and fully automated.
- All the above create poor stakeholder visibility, cost overruns, poor ROI, and loss of competitive momentum.
The Solution
MicroAI Launchpad is solving these development and business challenges by providing a fully comprehensive AI-enablement suite that shortens development time, reduces cost, minimizes risk, and provides a quicker time to market. Launchpad puts unparalleled capability and flexibility into the hands of the AI developer as well as the business process owner.
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