Hassle-free compliance monitoring, analysis, insights, and reporting all from one beautiful platform.

Compliance Monitoring Simplified


With growing environmental concerns, environmental agencies and governments around the globe are taking major steps towards reducing emissions, and holding organizations accountable. Our solutions are built to satisfy the most stringent regulations anywhere. From the US EPA to Singapore NEA, we can do it all.


Traditional PEMS solutions rely heavily on historical data, and as a result have trouble accurately predicting real-time emissions as seasons change, and equipment ages. Zuno uses Neural Network templates capable of predicting real-time values with over 98% accuracy. Time and time again.

Data Access Anytime, Anywhere


We know how important your data is and how critical your assets are. Our microservice architecture minimizes risk of attacks, and ensures your data remains encrypted end-to-end.

FLEXIBLE DEPLOYMENTS, SEAMLESS ACCESS offers the flexibility to deploy our solution on-premises, as well as on private cloud, and public cloud infrastructure. The user-friendly web interface allows customers to access their emission data, reports, insights and receive real-time alerts from any device, at any time. No more clunky workstations.

Interactive Dashboard Custom Reports


View interactive graphs, charts, and custom graphics tailored to your use cases. Create user specific configurations, alerts, reports, and control all your settings from our powerful data acquisition and handling system (DAHS) built for emissions monitoring.


As learns about your operations and processes, our powerful AI engine generates valuable insights into your operations and suggests possible improvements. Track the health of your critical sensors and get alerts on early signs of failure.

Want to see how it works?

Check out our video below

Play Video

Download our product sheet here

Frequently Asked Questions

Predictive Emissions Monitoring Systems (PEMS) are a software-based solution for emissions monitoring. PEMS is generally regarded as a cost-effective alternative to traditional hardware based Continuous Emissions Monitoring Systems (CEMS). There are three main model types used in PEMS – neural networks, first principles, and statistical hybrid models.

CEMS, or Continuous Emissions Monitoring Systems are hardware analyzer based solution for emissions monitoring. CEMS collect air samples from the emission source using probes, condensers, heated sample lines, and analyzers. The different types of CEMS can be catogorized into Dilution, Extractive and FTIR CEMS. is a neural network based PEMS. Here is a brief explanation on how it works:

  1. Data Collection
    First, Historical process and emissions data are collected.
  2. Model Training
    Next, Using deep learning techniques, the neural network learns correlations between the input process data and the emissions produced, building a predictive model. The model can be retrained easily as more data is collected, improving prediction accuracy.
  3. Deployment
    When deployed at a site, real-time process data is fed into the model and predicted emissions are generated. After that, an initial certification audit is performed where the predicted emissions are verified using reference methods (i.e: Mobile CEMS).

Compared to the CEMS, has the following benefits:

  • Low installation costs: fewer components and lower hardware requirements
  • High performance: accurate, reliable and consistent emissions monitoring
  • Low maintenance costs: minimal hardware, no moving parts
  • Resilient: able to detect and alert sensor failures, and operate in such events

Compared to the other types of PEMS, has the following advantages:

  • Resilient to sensor/input failures
  • Accurate predictions even on previously unseen input data
  • Easily retrained and updated
  • Provides optimization and improves efficiency

Want to see it in action?