We acknowledge the significance of Artificial Intelligence (AI) and Automation in propelling cognitive transformations for intelligent enterprises that focus on a digital-centric future. Our team specializes in establishing enterprise-wide ecosystems through end-to-end digitalization, providing advisory, implementation, and support services for intelligent automation. Our services encompass automating repetitive business processes in diverse areas such as finance, invoicing, marketing, and claims processing across industries. Our automation services integrate AI capabilities to optimize solutions and aid in driving operational excellence and maximization of return on investment (ROI). With our proficiency in AI and Automation, we can assist your enterprise to stay ahead of the curve and excel in the current digital landscape.

Our capabilities

Our automation services are designed to integrate analytics with Artificial Intelligence (AI) and industry-specific expertise, resulting in customized solutions that cater to the unique needs of our clients. We provide guidance in determining the most appropriate application for the solution, selecting the most suitable technologies, and ensuring its successful adoption across the organization. Our approach is designed to ensure that our clients not only have access to cutting-edge technology but also have the support they need to effectively implement and utilize it to drive business results.

AI Solutions

Solve your most important business challenges—fast.

Business process automation

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DWS SynOps

An innovative human-machine operating engine that optimizes people, technology, data and intelligence.


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Transform from data center to cloud-to-edge with DWS and VMware.

Hewlett Packard Enterprise


Unlock data value and drive innovative digital experiences with edge-to-cloud, as-a-service solutions.

AT&T Business


Innovate confidently with high-performance network services designed for next-generation solutions.



UiPath streamlines processes, uncovers efficiencies and provides insights DWS and UiPath.



Modernize, unify and secure your hybrid and multicloud environments with DWS and IBM.



Modernize for tangible cloud, workplace and application business results with DWS and Microsoft.

Amazon Web Services


Modernize, accelerate migrations and create cloud value with DWS and AWS.

Google Cloud

Google Cloud

Harness the combined power of Google Cloud and DWS expertise in managing mission-critical workloads and transformations.

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Our Customers

Our deep expertise in end-to-end marketplace solutions helps B2B & B2C e-commerce players alike







Frequently asked questions

AI automation refers to the use of artificial intelligence (AI) and machine learning algorithms to automate tasks and processes that were previously performed by humans.

The benefits of AI automation include increased efficiency, accuracy, and speed, reduced errors and costs, and the ability to handle complex and high-volume tasks.

Common use cases for AI automation include data processing, customer service, marketing and sales, and manufacturing.

AI automation works by analyzing data and making decisions based on that data, without human intervention. It is able to learn and improve over time through machine learning algorithms, making it more effective and efficient with each iteration.

Some of the challenges of AI automation include the need for high-quality data, the potential for bias in algorithms, and the need for ongoing maintenance and monitoring. Additionally, there may be concerns around job displacement and the need for retraining and upskilling of existing employees.

To implement AI automation in your organization, start by identifying tasks and processes that could be automated, assess the quality of your data, and choose the appropriate AI technology. Then, develop and test a proof-of-concept, and scale your implementation as needed.

The future of AI automation is likely to be focused on increased automation of more complex tasks, and the integration of AI technology into various industries and sectors. It is also expected to continue to evolve and improve through advances in machine learning and other AI technologies.

To ensure ethical and responsible use of AI automation, organizations should have clear policies and guidelines in place for data privacy, bias, and algorithmic accountability. Additionally, organizations should regularly evaluate the impact of AI automation on society, and work to mitigate any negative effects.