Running a wastewater treatment plant means constantly balancing two competing demands: energy consumption and effluent quality. Too little aeration and the water leaving your plant falls short of regulatory standards. Too much, and you're burning energy and budget on air that isn't needed. Finding the right operating setpoint has traditionally required deep modeling expertise, manual tuning, and hard-won operator experience. In this webinar, we show how the Dyad Agent changes that equation.
Using an activated sludge process model - one of the most widely used biological treatment systems in municipal and industrial wastewater management - we'll demonstrate how the Dyad Agent can simulate, interrogate, and modify a working process model in real time through natural language. You'll watch the Agent adjust model parameters, explain the physical consequences of those changes, and execute a full parameter sweep across aeration rates to map the tradeoff between energy input and effluent quality at the outlet.
The workflow on display here — modify, simulate, sweep, reevaluate operating conditions — is one that applies far beyond wastewater. Any engineer working with complex physical systems will recognize the challenge of identifying the right conditions to run them, and the opportunity that agentic simulation represents.
Key takeaways:
How the Dyad Agent modifies and re-simulates an existing process model through natural language
How sweep results give operators the insight to make confident setpoint decisions
What agentic AI-driven tradespace exploration looks like applied to real-world engineering models
