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Welcome to ScienceOps

ScienceOps creates, validates, and optimizes algorithms. We provide a competitive advantage to companies by developing algorithms and decision support systems that turn data into knowledge.

Algorithm Solutions

Our team of Ph.D. level scientists provides algorithm solutions for your business needs.
Enable your business critical code to produce required results faster, allowing better decisions and opening up new opportunities for your business.

Algorithm Development as Firm Fixed Price Contracts
3^rd Party Algorithm Validation
Algorithm Optimization
Statistical Data Analysis
Data Mining
Complex Algorithms
Scientific Algorithms
Custom Algorithms
Rapid Algorithm development
Algorithm Design

Customized Algorithms can read, search, analyze large amounts of information, make predictions, are able to make real time split second decisions and adapt and adjust instantly to changes in new input information.

Algorithm

At ScienceOps we define an Algorithm as being a programmatic solution to a scientific or business problem.

The algorithm, or programmatic solution, should do the following:

Provide new insights or better understanding to your business
Help you better utilize your resources
Be implementable in a common computing language

The algorithm might involve:

Applying existing techniques in new way
Modifying existing techniques
Developing new techniques

All aspects of developing an algorithm require broad knowledge in several disciplines and extensive experience in solving many different types of problems.

ScienceOps can solve your toughest problems because we provide:

Comprehensive experience and comprehensive solutions
Prompt solution development
The ability to outsource or augment your own research and development team

Below is an example of a programmatic solution to a business problem.

A software company for the lumber industry came to us with a question on how we might be able to help them better utilize the natural resource which was the basis of their business. They believed they were wasting more wood than necessary from the raw logs which they cut. After a close examination of the problem, ScienceOps determined that finding the optimal centerline of each log would allow the company to reduce waste and get the most profitable use out of each log. We were able to design an algorithm that more accurately approximated the actual log centerline and with its implementation in software many lumber companies are now benefiting by getting more product from their logs.