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PE

Predict Environmental Software

This company provides specialized software for modeling ion exchange (IX) consumption based on solution composition and material capacity. The platform incorporates mass balance equations to predict ion removal efficiency for various IX resin types, including SAC, WAC, SBA, and chelating resins. Users can model applications like water softening, demineralization, and metals recovery using pre-loaded or estimated resin performance data.

Calabasas, United StatesFounded 20232100+ followers
Updated 20 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Founder details are not available yet.

Product

Problem

Environmental projects involving activated carbon and ion exchange processes require complex modeling, often involving numerous steps and specialized expertise. This complexity can lead to delays, increased operational costs, and difficulty for non-technical users to obtain quick and accurate project insights.

Solution

PREDICT offers an AI-powered software solution that streamlines the modeling of activated carbon and ion exchange processes. By leveraging the Freundlich equation, machine learning, and pre-loaded data for over 100 ion exchange brands, PREDICT enables rapid modeling and cost estimation for environmental projects. The software simplifies complex calculations, allowing both technical and non-technical users to quickly assess project feasibility, optimize design parameters, and predict outcomes. PREDICT also includes a sludge generation calculator, which estimates solid waste volumes based on water contaminants and flow rates, aiding in project management and operational planning. Users can generate shareable reports with embedded information for collaboration with teams, clients, or regulatory agencies.

Target Audience

The primary target audience includes environmental engineers, project managers, and consultants involved in water treatment and remediation projects, as well as environmental scientists and regulatory agencies.

Features

  • Activated carbon modeling based on the Freundlich adsorption isotherm, experimental results, and AI-driven machine learning.
  • Ion exchange modeling utilizing material capacity, solution composition, and mass balance equations.
  • Pre-loaded capacity data for over 100 commonly used ion exchange brands.
  • Sludge generation calculator for estimating solid waste volumes based on water contaminants and flow rate.
  • Report generation feature for sharing modeling results with teams, clients, or regulatory agencies.
  • Supports modeling for various ion exchange resins, including Strong Acid Cation (SAC), Weak Acid Cation (WAC), Strong Base Anion (SBA), Weak Base Anion (WBA), and Chelating resins.
  • Models the use of Polymer Catalysts for organic contaminants.
This profile is AI-generated and may contain inaccuracies.