Jumpstart your digital transformation with KOMPASS and
achieve over 50% reduction in implementation cost and 70%
improvement in process efficiency.
The rapidly increasing intricacies of managing day-to-day operations have compelled companies to look at ways to reduce operational bottlenecks through digital transformation. Organizations are considering automating the lion’s share of the routine tasks to bring about enhanced efficiency.
The feasible approach is to use microservices and integrate them using robotics and automation. We facilitate this via our unique solution architecture – KOMPASS.
KOMPASS is a multi-layered and composable architecture with a stack of connectors and orchestrators. This repository is built on an open framework using the industry best practices. Since the architecture is preconfigured and predefined, it can be connected to any technology stack.
With digital data expanding from databases and data warehouses to wearables, social media, lab test data, government data etc., the sources to capture and store these data have multiplied. It is not feasible to use the plethora of information directly in the current systems. KOMPASS uses intelligent algorithms to integrate all the source data and convert it to valuable real-time data using connectors and process flow designers.
structure or unstructured application or interface.
designer making it easy to configure, integrate and
operate from a single interface.
accelerators and connectors which enable faster
configuration and deployment.
data warehouses, data lakes, & unstructured data
sources, thereby creating a data fabric for central
data flow and co-ordination.
a codeless hyper automation enabled using natural
language which amplify the ability to automate
complex multiprocess tasks.
automation with machine learning predictive
analytics capabilities.
based tool box used to deliver high value
optimized, customer experience.
dashboards delivered through agile platforms
The rapidly increasing intricacies of managing day-to-day operations have compelled companies to look at ways to reduce operational bottlenecks through digital transformation. Organizations are considering automating the lion’s share of the routine tasks to bring about enhanced efficiency.
The feasible approach is to use microservices and integrate them using robotics and automation. We facilitate this via our unique solution architecture – KOMPASS.
KOMPASS is a multi-layered and composable architecture with a stack of connectors and orchestrators. This repository is built on an open framework using the industry best practices. Since the architecture is preconfigured and predefined, it can be connected to any technology stack.
With digital data expanding from databases and data warehouses to wearables, social media, lab test data, government data etc., the sources to capture and store these data have multiplied. It is not feasible to use the plethora of information directly in the current systems. KOMPASS uses intelligent algorithms to integrate all the source data and convert it to valuable real-time data using connectors and process flow designers.
structure or unstructured application or interface.
designer making it easy to configure, integrate and
operate from a single interface.
accelerators and connectors which enable faster
configuration and deployment.
data warehouses, data lakes, & unstructured data
sources, thereby creating a data fabric for central
data flow and co-ordination.
a codeless hyper automation enabled using natural
language which amplify the ability to automate
complex multiprocess tasks.
automation with machine learning predictive
analytics capabilities.
based tool box used to deliver high value
optimized, customer experience.
dashboards delivered through agile platforms
and reporting
The amalgamation of AI and RPA molds the business process to become more agile and responsive. The easy-to-use plug-and-play functionality guarantees faster implementation and deployment, and a significant reduction in process time with substantial improvement in accuracy of reporting.
