Effex provides a SaaS platform for Design of Experiments (DoE) that minimizes experimental effort while maximizing knowledge discovery. The software delivers optimal experimental designs, including proprietary OMARS designs, tailored for specific process improvement challenges. This approach reduces resource consumption, accelerates time-to-market, and facilitates the discovery of best operating conditions and factor interactions.
Funding
Funding not disclosed
Founders
Product
Problem
Experimentation in industries like life sciences, food, chemicals, and semiconductors often involves complex processes with numerous interacting factors, making it difficult to efficiently identify optimal conditions and maximize knowledge discovery. Traditional Design of Experiments (DoE) methods can be inefficient, requiring extensive trials and failing to capture all possible interactions between variables. This leads to increased experimental effort, higher costs, and slower innovation cycles.
Solution
Effex is a cloud-based Design of Experiments (DoE) platform that leverages Orthogonal Minimally Aliased Response Surface (OMARS) designs to streamline experimental planning and optimization. The platform enables users to efficiently compare thousands of experimental designs, identify interactions between multiple factors, and select the best models for their specific problems. Effex minimizes experimental effort, maximizes knowledge discovery, and facilitates collaboration through its cloud-first environment, helping teams across various industries accelerate innovation and improve product and process outcomes.
Target Audience
The primary target audience includes scientists, engineers, and researchers in industries such as life sciences, food, chemicals, automotive and semiconductors who are seeking to optimize their experimental processes and accelerate knowledge discovery.
Features
- Cloud-based platform for collaborative experimental design and analysis
- Access to a catalog of exclusive OMARS designs for efficient experimentation
- Ability to compare thousands of designs considering multiple criteria simultaneously
- Identification of interactions between variables to optimize resource use
- Built-in experiment management, traceability, and calculation tools
- Graphical and recommendation algorithms for selecting the best models
- Capability to explore competing optimal combinations of factor values
- Data import from external sources like Excel
- Secure data storage on AWS with isolated cloud storage instances