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Aitomatic

The Knowledge-First App Engine for Industrial AI
United States
2021
Private
< $10m
11 - 50
Open website

For teams with insufficient data & labels to build ML solutions, Aitomatic Knowledge-First App Engine is the answer. Instead of wasting money and time to get more data, AI teams use Aitomatic to leverage domain expertise already present in the organization.

Our technology helps enterprises encode domain expertise, combine ML, and automate everything. Led by Google, Amazon and Apple veterans—with 100 person-years Panasonic Industrial-AI experience—we bring a unique combination of AI-engineering tech and a deep understanding of your challenges. W

e’re the team named FastCompany’s Top-10 Most Innovative. We create and maintain the open-source project Human-First AI.

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AI, Industrial AI, Machine Learning, Predictive Maintenance, Demand Forecasting, Energy Optimization, IoT, Systems of Intelligence, AI Engineering, and Knowledge-First AI

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Aitomatic’s Technology Stack maps Aitomatic’s participation in the IoT technology stack.
  • Application Layer
  • Functional Applications
  • Cloud Layer
  • Platform as a Service
    Infrastructure as a Service
  • Edge Layer
  • Automation & Control
    Processors & Edge Intelligence
    Actuators
    Sensors
  • Devices Layer
  • Robots
    Drones
    Wearables
  • Supporting Technologies
  • Analytics & Modeling
    Application Infrastructure & Middleware
    Cybersecurity & Privacy
    Networks & Connectivity
Technological Capability
None
Minor
Moderate
Strong
Number of Podcasts1
EP 136 - How human-first AI creates better algorithms - Christopher Nguyen, CEO & Co-Founder, Aitomatic
Friday, Jul 08, 2022

How can industrial organizations optimize AI’s potential to build powerful operational capabilities? Leveraging their existing domain expertise is the key. Aitomatic helps companies level up their AI’s competitive edge by combining human and artificial intelligence.  

In this episode, we sat down with Christopher Nguyen, CEO and Co-Founder of Aitomatic, a knowledge-first app engine for industrial IoT that assists industrial companies in using their domain expertise to build more effective algorithms. We discussed why only 9% of manufacturers currently use AI in their business processes and how they can overcome data availability challenges. We also explored which use cases are best suited for a human-first AI development platform, and which work well with a traditional black box training approach. 

Key topics: 

  • Why are we not seeing AI takeoff in the industrial sector as often as we see it in consumer markets? 
  • What are the limits of modern AI solutions in enabling predictive and prescriptive analytics use cases?
  • How can you manage the fundamental challenge of small data sets?
  • How can your engineers and operators embed their know-how in an AI algorithm? 
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