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Google Cloud Platform > Case Studies > RandomTrees + Looker: Accelerating and Enabling Enterprise AI
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RandomTrees + Looker: Accelerating and Enabling Enterprise AI

Technology Category
  • Analytics & Modeling - Machine Learning
  • Application Infrastructure & Middleware - API Integration & Management
Applicable Functions
  • Maintenance
Use Cases
  • Asset Health Management (AHM)
  • Predictive Maintenance
Services
  • Data Science Services
  • System Integration
The Challenge
Businesses require critical equipment to be running at peak efficiencies and utilization in order to realize return on capital investments. In the digitally connected world, businesses face higher operational risks due to unexpected failures and quite often have limited insights into the root cause of problems. Common industry challenges are: Costs of unproductive time, Lower asset utilization, Risks of operating outside of manufacturer specifications, Regulatory compliance risk.
About The Customer
RandomTrees is an AI company with a mission to create a climate that empowers enterprises to realize business outcomes. Their advisory services help clients to embark on business excellence journeys using AI with a proven methodology. Their delivery services provide the know-how across AI platforms, data engineering, and process expertise to build, run, and operate AI solutions.
The Solution
RandomTrees’ AURA™ is a suite of AI solutions that are platform agnostic and a ReadytoRun AI suite that can be augmented to supply chain, asset lifecycle management (ALM), customer relationship management (CRM), and computer vision systems. Looker and RandomTrees work together to accelerate and enable enterprise AI. By integrating Looker with RandomTrees AI suite, customers are able to improve the speed of creating AI-ready data. The insights generated by AURA are easily explained by a slick chat bot integration, and actions taken by users are integrated with enterprise systems.
Operational Impact
  • Democratization of data preparation activities for citizen scientists
  • Addition and integration of AI layers such as Chatbots
  • Integration of Looker with deep learning systems
Quantitative Benefit
  • Reduced data preparation time
  • Ease of integration with enterprise systems
  • End users empowered with advanced data tasks

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