Rainbird

Rainbird is an award winning Artificial Intelligence platform that makes the business operations smarter. It enables enterprises to build systems with human-like decision making abilities resulting in greater efficiency and increased quality.

Rainbird enables users to take existing, human, business knowledge and combine it with the company’s data to automate knowledge work and deliver consultative systems that can transform the way the company’s staff and customers interact with each other.

Rainbird is at the forefront of knowledge work automation technology. It is a powerful ecosystem for re-engineering knowledge work enabling companies to automate and augment the work their staff’s performance.

Rainbird enables the modeling of a new generation of problem solving tools, accessible to both agents and customers. The result is a reduced time to competence, quicker mean time to resolution, and a substantial increase in service standards. When it comes to managing the sales team, Rainbird enables its users to combine nuanced, human knowledge with the company’s transactional data – to scale expertise to the enterprises entire sales force. Make the newly recruited sales staff as effective as most seasoned sales people.

Rainbird helps transform company’s operations by augmenting the human knowledge workers with powerful tools. Rainbird stitches multiple systems together enabling users to automate repetitive tasks. Rainbird is enabling expertise to be embedded in business systems.

This is leading to more efficient and consistent knowledge-work. Businesses can use Rainbird to create systems capable of making nuanced decisions that learn from outcomes and challenges. Rainbird can model and track business governance and compliance obligations and integrate the logic into the business processes utilizing real-time data. The result is greater operational compliance, reduced costs and fewer breaches.

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More Information on Predictive Analysis Process

Predictive Analytics Process Flow

For more information of predictive analytics process, please review the overview of each components in the predictive analytics process: data collection (data mining), data analysis, statistical analysis, predictive modeling and predictive model deployment.