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What We Deliver



What We Deliver
Organizations thriving on scientific research and innovation are always evolving in the face of an ever changing customer needs and peer competition. The faster these organizations bring their innovations to the market greater the opportunity for them to capitalise on their investments. The stake holders of research & innovation in these organisations are constantly challenging their knowledge and processes to make them more efficient and effective in delivering new discoveries.

Research and innovation processes are dependant on knowledge, experience and ability of an individual or group of individuals in an organization. In a scientists lab the tested route of problem solving involves defining a problem, identifying the cause of the problem, generating various hypothesis to address the problem screen and prioritizing a select set of hypothesis then perform experiments to arrive at a solution. This process though straight and simple to navigate becomes challenging when not backed by sufficient data / information.

To leverage on information and deliver competitive advantage, enterprises need to move out of traditional documentation processes and formulate and deploy disruptive digital technologies that help capture laboratory data, information and knowledge into a system where it is easy to search, reuse and share across the organization which contributes not only significant operational and productivity enhancements but also sustainable innovation.

Swastik Innovistaz brings some of these cutting edge predictive sciences solutions to our clients by partnering with few of the best in this business. Our predictive sciences solutions are broadly categorised into Predictive Modelling Sciences and Predictive Data Sciences:
Predictive Modelling Sciences:

Predictive capability is driving the transformation of technological innovation. New materials and chemical processes are needed to meet demanding performance requirements across the broad spectrum of advanced technologies. It is a known fact that development of new materials, from discovery to deployment, typically required two decades.

Predictive modeling guides experiments in the most productive directions, to accelerate design and testing, and to understand performance. State-of-the-art computational tools allow scientists to calculate from first principles the interactions that dominate molecular behavior, while experimental tools can provide time-resolved measurements on real materials to validate these models.

Success of Predictive modeling in several industry sectors have demonstrated significant return on investment and reduced development times.

Molecular Modeling and Simulation Software
Life Sciences           Materials Sciences

Research and innovation processes are dependant on knowledge, experience and ability of an individual or group of individuals in an organization. In a scientists lab the tested route of problem solving involves defining a problem, identifying the cause of the problem, generating various hypothesis to address the problem screen and prioritizing a select set of hypothesis then perform experiments to arrive at a solution. This process though straight and simple to navigate becomes challenging when not backed by sufficient data / information.

Predictive Data Sciences: Research Informatics

Knowledge management is the process of capturing, developing, sharing, and effectively using organizational knowledge.

Industries driven by science need to survive and deliver in an extremely competitive environment, which calls for the need to optimized operations, ever improving efficiency without compromising quality and adhering to regulations as well as drive innovation. These challenges also apply to the labs in academic and government setups, which in order to contribute to the organizational goals needs to remove inefficiencies and compliance risks from lab processes and create an environment conducive to collaborate for increasing innovation rates.

Collaboration within and between the labs will be achieved by eliminating paper-based experimental documentation processes that present lot of challenges to compliance but also offer difficulties access of relevant data throughout the research, development and manufacturing lifecycle which is vital to hone an environment which encourages collaboration in order to drive innovation, to rationalize research processes and make informed decisions whenever called for during the product development process.

Saas Based Lab Informatics for R&D
To leverage on information and deliver competitive advantage, enterprises need to move out of traditional documentation processes and formulate and deploy disruptive digital technologies that help capture laboratory data, information and knowledge into a system where it is easy to search, reuse and share across the organization which contribute not only significant operational and productivity enhancements but also sustainable innovation.


Training: Please write to us to know more about these services.