Rules Engine

Explainable GenAI

a fusion of causal modeling and GenAI

Billions have poured into GenAI, prompting major tech players to explore its full potential. However, its adoption in industrial settings faces significant hurdles, notably the "hallucination" issue. Leveraging GenAI for problem-solving necessitates a clear understanding of the problem at hand. Current GenAI initiatives primarily focus on tasks like knowledge modeling but often fall short in grasping problem complexities, leading to hallucinations or irrelevant outputs. Waylay pioneering approach tackles these weaknesses head-on, by integrating real time data, causal graphs and outcome insights into the training process. We combine historical records/manuals with real-time machine data to find the root cause and provide the right remedy - reducing the risk of human error, ensuring consistency that allows human workers to focus on more complex and strategic aspects of their jobs.

Learn more - documentationWaylay - AI Labs

Waylay Automation/Rules Engine

Over the past decade, our automation platform has undergone continuous innovation and evolution. We have incorporated cutting-edge technologies, such as artificial intelligence and machine learning, to enhance efficiency and drive digital transformation. Throughout this journey, the platform has empowered businesses across diverse industries, making automation a cornerstone of streamlined processes and intelligent decision-making.

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Modeling Complex Logic

Real life is multivariable.

  • Combining multiple non-binary outcomes of functions (observations) in the rule, beyond Boolean true/false states.
  • Dealing with majority voting conditions in the rule.
  • Handling conditional executions of functions based on the outcomes of previous observations.

Modeling Time

Time adds complexity.

  • Dealing with the past (handling expired or soon-to-expire information).
  • Dealing with the present (combining asynchronous and synchronous information).
  • Dealing with the future (forecasting for prediction and anomaly detection).

Modeling Uncertainty

Uncertainty is unavoidable.

  • Dealing with noisy sensor data and missing data.
  • Dealing with unstable wireless sensors, fully dependent on battery lifespan.
  • Dealing with intermittent network connectivity or network outages.

Deploy at Scale

Explainable GenAI

Book a demo - it's free

Waylay Approach: a fusion of causal modeling and GenAI  

Billions have poured into GenAI, prompting major tech players to explore its full potential. However, its adoption in industrial settings faces significant hurdles, notably the "hallucination" issue. Leveraging GenAI for problem-solving necessitates a clear understanding of the problem at hand. Current GenAI initiatives primarily focus on tasks like knowledge modeling but often fall short in grasping problem complexities, leading to hallucinations or irrelevant outputs. Waylay pioneering approach tackles these weaknesses head-on, by integrating real time data, causal graphs and outcome insights into the training process. We combine historical records/manuals with real-time machine data to find the root cause and provide the right remedy - reducing the risk of human error, ensuring consistency that allows human workers to focus on more complex and strategic aspects of their jobs.

01 | Low Code GenAI API builder (LLM neutral)

In under an hour, you can construct a single-entry API endpoint capable of unleashing the full potential of GenAI in conjunction with any third-party API endpoint, seamlessly integrating it into your application. Additionally, you can design an intuitive interface offering multiple choices, all while retaining complete control over the responses, which are subsequently directed to various LLM endpoints—whether with or without RAG — allowing for management of the generated responses. This streamlined process mirrors the architecture behind the Waylay Rules Explainer.

02 | Conversational Apps and Bots

Easily integrate any third-party APIs into your conversational bot with just a single click. Unlike traditional conversational bot development, often taking weeks or even months, the ability to swiftly create LLM-neutral bots enables organizations to deploy solutions rapidly. This agility allows businesses to address immediate needs and respond promptly to evolving market demands, staying ahead of the curve in today's fast-paced digital landscape.

03 | Building mult-agent GenAI apps

Building multi-agent GAI applications involves creating systems that can perform tasks across various domains and interact with their environment and each other autonomously. These applications have the potential to revolutionize various industries by enabling intelligent systems to work together autonomously to achieve complex goals. With Waylay, you can orchestrate different GAI agents and deploy new apps in few hours.

How it works

Use Cases

We're thrilled to share with you the new and cool developments that will redefine the way we operate and engage. From cutting-edge technologies to transformative strategies, join us on this forward-looking adventure as we shape a year filled with excitement, innovation, and remarkable achievements. Buckle up for a thrilling ride into the future of what's next! 👇

Industrials - the right remedy in any language

We combine historical records/manuals with real-time machine data to find the root cause and provide the right remedy in any language - reducing the risk of human error, ensuring consistency that allows human workers to focus on more complex and strategic aspects of their jobs. More about this you can find in this blog post or in this video.

Fintech - Bots powered by GenAI: A Shift from Case Management Tools

The advent of intelligent bots is poised to reshape the landscape of financial services, prompting a reevaluation of traditional case management tools and revolutionizing the entire fraud prevention process. More about this you can find in this blog post or in this video.

How it works

Use Cases

Seeing is believing, so take a look at what our platform can do.

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Any To Any Workflow Orchestration

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