The Problem: 

Every system developer knows that software and hardware complexity is increasing exponentially and traditional approaches to building systems struggle to keep pace with real-world demands.

Classical system design relies on integrating multiple software and hardware packages to achieve design requirements. However, these methods often fail to address:

• Unpredictable workloads, leading to configuration conflicts and resource misallocations.
• The complexity of AI compute itself, which can complicate design due to its probabilistic nature.
• Sometimes, users later force unintended operations, software code is conflicted, desired maintenance practices differ or the hardware is mis-applied or degraded for the conditions being experienced.

Even optimization practices such as inference, simulations and feedback loops can anticipate expected outcomes but leave systems vulnerable to unexpected or unanticipated events, leading to sub-optimal performance, increased risks of bugs and costly recalls or outages.

The Solution:   

The basic idea is to make any configuration space variable, apply goals as first class objects under software control and then configure on the fly based upon the workload at any instant. Goals let the system reason about its current condition as it seeks optimal solutions from the available system resources.

The Company’s proprietary technology transforms classical configuration practices to Self-Aware™ computing, a universal computational method for dynamically configuring systems to actual workload conditions each instant, using administratively set goals.

In a major breakthrough, Self-Aware™ technology has been applied to AI itself, AdaptiveAI™, inviting a new generation of configurable capabilities, now tunable by goals:

• Self-Aware inference 
• Self-Aware agents
• Self-Aware neural network training architectures

The Sequitur™ Platform, Config’s flagship product, is the world’s first Self-Aware™ computing platform, providing developers with:

• APIs for real-time access to system data and configuration tools.
• Digital twin simulations for configuration testing and optimization.
• Run-time optimization methodologies for adaptive performance.

Benefits:

Overall, Self-Aware™ configuration technology lowers development costs, reduce the risk of conflicts and system failures and provides better outcomes using AI.

System investments can be better future proofed to meet new requirements by simply changing goals, without re-training or re-engineering.