OPTaaS: Optimization as a Service

Bayesian Optimization via web-services

OPTaaS is a general-purpose Bayesian optimizer which provides optimal parameter configurations via web-services. It can handle any parameter type and does not need to know the underlying process, models, or data. It requires the client to specify the parameters and their domains, and to post back the accuracy scores for each of OPTaaS’ recommended parameter configurations. OPTaaS uses these scores to model the underlying system and search for optimal configurations faster.

Optimization constitutes an integral part of every business problem. A process or product will not operate as fast, well, or productively as possible if its parameter configurations are not correctly optimized. Sub-optimal operating conditions will not always impact overall operations, but in certain industries this can lead to lost revenue, unnecessary costs and an overall drop in competitiveness. Moreover, business processes are often complex, resulting in a combinatorial explosion of possible parameter configurations. In such cases, optimization is either random, manual or foregone as its costs, in both computation and time, are typically high. OPTaaS aims to make optimization efficient for industries where processes are complex, expensive to explore, and require constant tuning due to changing environmental conditions.

OPTaaS Automatically Optimizes:

• Any black box process
• Data Science pipelines
• Machine Learning/Deep Learning models
• Financial models, Back tests

The Process:

• Client requests parameter configurations and posts back the scores for the associated parameters
• OPTaaS uses the scores to recommend new parameters & probabilistic modelling to maximise the efficiency of the optimization process


Better Results

Faster Tuning

Cheaper Development

Remove the pain of coding


• Unlimited parameters per optimization task
• Integer, numeric, Boolean and categorical parameter types
• Flexible parameter constraints
• Seamless integration via simple API
• OPTaaS never sees your models or data


• Removes the pain of coding with automatic web-services
• Makes your models evergreen cost-effectively
• Reduces the time and cost of identifying optimal parameter configurations
• Frees up valuable time for Data Scientists to focus on extracting insights

Further Information:
White Paper

Bayesian Optimization for Dynamic Problems
Distributionally Ambiguous Optimization for Batch Bayesian Optimization
Fast Information-theoretic Bayesian optimisation
Raiders of the lost architecture: for bayesian optimization in conditional parameter spaces
Optimization, fast and slow: optimally switching between local and Bayesian optimization

Sign up for a demo now: optaas@mindfoundry.ai

Want to work with us?