The challenges with traditional RPA

While RPA (Robotic Process Automation) is arguably the most widely adopted automation technology, it takes a lot to manage and scale an efficient, enterprise-wide Intelligent Automation (IA) environment where the digital workforce makes an impact.

Key challenges with traditional RPA include:

It automates tasks, not processes

Traditional RPA provides task-based automation, instead of automating processes across the enterprise

It’s just not scalable

RPA doesn’t scale to enterprise levels. Without scalability, businesses can’t justify the
significant investments

High cost of integration

Traditional RPA needs to integrate with OCR/ICR and AI/ML technology providers, which is expensive to integrate

RPA needs structured data

RPA relies heavily on the availability of structured data and falters when it has to handle semi-structured or unstructured data


Turbocharge RPA with Digital Workforce Management (DWM)

Part of the ANTsteinTM integrated automation platform, DWM turbocharges digital transformation and efficiency across your enterprise. DWM effectively blends human and ‘virtual’ workers, giving employees the chance to use their ingenuity, creativity, and empathy to collaborate.

DWM capabilities

Build your digital workforce BOTs easily and quickly in a low code/no code environment, at relatively low cost with:

  • Cognitive BOTs that respond dynamically to changes in the operating environment

  • Real-time management and deployment of multi-skilled BOTs to undertake many different tasks without human intervention

  • Multi-tenancy that allows multiple BOTs to reside on a single machine and perform multiple processes simultaneously


DWM provides:

  • A highly secure credential vault that is encrypted for superior data security

  • Business continuity planning allows self-recovery from any infrastructure failures

Bring intelligence to intelligent automation and build a combined human and digital workforce with ease and speed

DWM benefits your enterprise

DWM synthesises the best of RPA, Artificial Intelligence and Machine Learning... but what does that actually mean in terms of business benefits?

Enterprise-wide scalability

Get away from RPA’s task-based mindset and scale automation across the enterprise

Ease and speed of implementation

Increase the speed and efficiency of implementation and ensure rapid ROI

A collaborative workforce

Create a work environment that leverages both human and digital workforces

Business continuity

Enable real time business  and mitigate risk management for your digital workforce

The Techy Bit - Key features

Each QueenBOT has the capacity to configure up to 50 ANTBOTs. With a low code/no code BOT development environment, multitenancy architecture and cognitive responsiveness QueenBOT provides real-time digital workforce management.

  • QueenBOT’s ability to log the results of execution of every step of an automated process gives unprecedented audit and analysis capabilities to grow your business
  • Enables Digital Operations Management and Data Transportation through intelligent BOTs by minimising downtime
  • With Cognitive BOTs, you’ll keep your productivity at the highest levels with BOTS that respond dynamically to operating environment changes
  • Multi-skilled BOTs provide profile flexibility, undertaking multiple processes using a single BOT
  • BOT productivity is built-in, with features such as availability-based trigger and message-based BOT trigger for deployment
  • Multitenancy architecture means you can maximise the value of your IT infrastructure investments with multiple BOTs residing on the same machine and performing different processes simultaneously
  • Failover provides self-recovery from infrastructure failures such as network, database or hardware downtime, ensuring business continuity
  • Process Discovery records, aggregates, animates and analyses user actions to accelerate your process analysis

"Our proprietary machine learning engine, the only one powered by fractal science, makes the adoption of machine learning a lot more efficient. As a science, it lends itself to smaller data sets for high yields of learning and lighter infrastructure for deployments, making machine learning more affordable for businesses and easier and faster to deploy."

Asheesh Mehra

AntWorks Group CEO and Co-Founder

Data Digitisation and Curation

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Enterprise AI and Machine Learning

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