Optym employs a wide variety of specialized expertise to build decision automation and optimization solutions. Building these systems requires specialized skill sets and Optym has put together a team with the ability and passion to develop such systems in rapid development mode.

Subject Matter Expertise

Subject matter expertise in the area that we are trying to automate is very important, as decision in various industries must honor certain resource constraints and optimize certain goals. To automate decision making, we need to know how decisions are made. Thus, our team works very closely with businesses and our clients to understand all aspects of the business problem and document it. We ask a lot of questions to develop a deep understanding of the subject areas.

However, learning how decisions are currently made is not sufficient. We need to be creative enough to determine how decisions should be made. We propose if there is a better way of doing tasks. As Henry Ford once said, “If I had asked people what they wanted, they would have said faster horses.” Being creative and coming up with a better way of decision making is an essential part of our delivery.


Data is not just numbers; it is the story of a business process. We analyze the data to get insight into the business process and this insight leads to the development of correct decision engines. Our team is well versed in data analytics, data treatment, data storage in databases and data retrieval through efficient query design. Use of big data techniques is also one of our core skill sets.

A decision automation system receives data from multiple applications and writes data into multiple applications – after all, it is just one piece of the puzzle. This data must be retrieved from a database then written into a database and it needs to be an efficient process. Thus, good database design and efficient processing of the data is very important. This requires a deep understanding of database technology.

Sometimes the data available for decision making is incomplete or incorrect. Sometimes the data coming from multiple sources is inconsistent. This is why we do data treatment before it can be consumed by decision modules. This is an essential part of building decision automation systems.

Operations Research

Most of our decision automations are in the field of scheduling, which includes some of the most challenging decision problems due to variability built into constraints that a schedule must satisfy and trade off between multiple objective functions. Through decades of research and development, we have developed a specialized technical procedure for solving complex scheduling problems, which we bring to each of our projects as a starting point and enhance it further. Our team has won several prestigious prizes in the field of operations research.

Operations research techniques are the brains behind our decision automation engines. We use both optimization and simulation techniques to solve decision problems. Our advanced formula is a novel combination of time-space networks, mixed integer programming (MIP), heuristics and iterative improvement techniques. We have had considerable success in using simulation-guided optimization techniques to solve scheduling problems.

Computer Science

When we have developed a technique to solve a business problem, it needs to be implemented. The implementation can make or break the system. If, for a real-time application, the decision engine takes five minutes, it will not be used; but if it takes less than five seconds, it can be used. Using the right data structures to implement an engine, writing efficient code and using parallel computing can have a significant impact on the running of a decision engine. Data mining and machine learning are also used in decision engines. Our team is well versed in these computer science techniques and uses them extensively in our software development.

By recruiting specialized computer science gurus with advanced degrees, we ensure that we have an infusion of the latest technological developments to our company. As well, we hold internal workshops on emerging topics so that we continue to disseminate these developments among other team members and keep them current.

Information Technology

Our decision engines are packaged within interfaces that are intuitive and easy to use. Our company has invested heavily in building a framework for developing enterprise-level decision automation systems that are highly reliable and have a high uptime (99.9%). Here are some examples of our commitment to building quality solutions.

Software Architecture

We have a team of highly experienced software architects, which ensures that our software solutions are designed for reliability and scalability.

Application Development

We develop desktop and web applications. We also build mobile applications for different operating systems such as iOS, Android and Windows.

Human Computer Interaction (HCI)

We take user interface design and user experience seriously, so we have a team of graphic designers and HCI specialists that participates in every project.

Recyclable Modules

We have developed a library of software modules and components that can be used by multiple projects. Use of this library reduces development time and cost.


All of our software is well documented and well commented so that it becomes person-independent and can be maintained in the long run.

Quality Assurance

We use the industry’s best practices for testing and quality assurance.

Project Management

Great project management is critical for the success of any project. After all, our work is about being on time, meeting budget constraints and satisfying end-user requirements. We follow the best agile practices and toolsets to track all project requirements, priorities, resources and releases, and we provide clear visibility on project progress for the stakeholders while maintaining consistent timely releases.

Planning is everything in our project management. We review requirements and designs thoroughly and lay out the project vision and projected development plan iteratively throughout the development life cycle of our projects to make sure the right problems are solved in the right order. We also continue to improve our development velocity with frequent reviews with all parties in the project.

We maintain high quality standards in all phases of project development with thorough code reviews, automated testing and several levels of functional and acceptance testing before we approve a release for production deployment. We continue to improve our processes with several quantitative measurements as part of our development standards.

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