AI Ecosystem

AI Ecosystem

What a long, strange trip it’s been! Rule4’s founders originally began work in AI when now-defunct Thinking Machines Corporation introduced the Connection Machine (CM2) in 1987.

Today, AI is ubiquitous in the road maps of next-generation technology initiatives. Availability of inexpensive, easy-to-use machine learning (ML) engines has made the core algorithms accessible to developers in a wide array of industries.

However, a full AI ecosystem is much broader than just the ML engine. Whether your application of AI involves tasks such as speech recognition and natural language processing (NLP), image analysis and recognition, or complex data analytics and prediction, it takes a village of subsystems to support the AI function, including:

  • Configuration
  • Data collection
  • Data verification
  • Feature extraction
  • Machine resource management
  • Process management tools
  • Analysis tools
  • Cybersecurity protection
  • Integrity protection
  • Server infrastructure (and auto-scaling)
  • API management
  • Monitoring
  • SSDLC
  • Data retention

. . . to name a few. Deploying and operating AI within your environment involves architecting a modular ecosystem where these subsystem components can be managed through their lifecycle in a way that increases supportability and reliability. This approach results in AI providing predictable, provable value to your organization.

Rule4 brings together the best in full-stack lifecycle management with deep AI understanding  to help deploy this powerful technology effectively. We’re here to help your organization craft an AI ecosystem you can depend on. Contact us today.