Building the Digital Future with AI Driven Autonomic Operations


Prakash Prabhu – Chief Business Officer & Co-Founder, VisionBot

We have seen how Visionbot™ can take your visual inspection monitoring to the next level. With Visionbot™, you can automate those manual workflows using AI and Deep Learning. It’s like having a super-smart assistant that can detect objects, events, and anomalies in real-time. And get this, it works with your existing fixed video cameras, so you don’t need to invest in any additional hardware

Imagine this: Most of your operational workflows are already semi-automated and captured by your ERP system. How about unifying multiple data points generated within all your business processes with the power of Visual AI. The autonomic enterprise is a self-optimizing business that applies AI and automation to decisioning, operations, and servicing across the organization.

You can get real-time reports and alerts from the field or shop floor without any hassle. Field workers can simply send and get reports over images, videos, or text while on duty. Visionbot™ will do its magic, leveraging AI and Deep Learning to analyse and detect any issues or anomalies. This frees up your field workforce and supervisory staff to focus more on their core tasks and services. No more wasting time on manual reporting and supervision.

Business operations in any agile enterprise is a combination of processes, interactions and activities that result in products services and information, and ultimately provide value to customers and stakeholders of the organization. Automation of business operations tends to be relatively based on historical processes with adaptability based on anticipated conditions. Autonomic business operations extend this by evaluating current and changing processes with more adaptability based on changing conditions.

When you unify Visual AI with data driven process automation, you leverage Inferential and Generative AI techniques that optimize and automate back-end processes at scale.

At Visionbot™, we work on deep learning and various implementations of GANs to enhance operational efficiencies in core areas of construction, manufacturing, logistics, retail and many more verticals.

The incremental journey to an autonomous enterprise is not a leap but a consistent shift

  1. Manual-led: Where people make most decisions, performing all functions.
  2. Automated: Where tech handles routine while people take on non-routine actions for scale and efficiency.
  3. Self-learning/ AI-guided: Where tech provides the real-time insights people need to make decisions for relevance and speed.
  4. Self-optimizing: Where tech drives agility autonomously while people focus on innovating to meet enterprise-wide objectives.

Enterprise owners and technology innovation leaders wanting to exploit emergent autonomic business operations trends should:

  • Create visibility and understanding of internal operations that underpin operational excellence and external interactions as represented by customer journey models. Do this by discovering exceptions and shadow operations with process mining, and providing input to the Autonomic operational process.
  • Operationalize the design of risk, compliance and, by extension, sustainability controls through understanding and connecting these controls to the day-to-day business operations.
  • Explore the path from autonomous business operations to autonomic business operations – the automation of automation, or automation with limited human intervention. According to Gartner research by 2024, 25% of global enterprises will have embraced process mining as a step-up to autonomic business.

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This means showing adaptive behaviour and aiming to enhance adapt ability and resilience of an organization by delivering continuous insights, guidance and actions connected to the actual situation (current state), targeted at a new operating model (future state), and driven by decision support capabilities (AI data driven).

Business operations resilience

Based on available day-to-day operational data, process mining tools continuously seek and find the relevant objective operational data. The advanced process mining algorithms then provide an accurate model of the ways of work in a format that can be understood by anybody in the organization.

Autonomous business operations resilience

Adding execution or automation capabilities to the mined data allows for an autonomous way of handling this operation. Autonomous does not relate to outcomes and only acts within predefined patterns or predefined rules that limit the change to processes, activities and/ or information.

Autonomic business operations resilience

Through providing awareness and learning capabilities, the full resilience life cycle is handled in an autonomic way. Autonomic implies the ability to adjust the structural rules or patterns based on the observed changes in the real-world process activity versus the historical baseline context within a business operations model.

Autonomic business operations will have considerable impact in many business areas.

  • Operational excellence.
  • Customer experience.
  • Risk and compliance.
  • Sustainability
  • Automation

EXAMPLE : AI driven Autonomic operations

Optimization of Production Schedule

It can analyse thousands of Production Scenarios and create valid and optimal plans/ schedules that maximizes yield while improving other important production outcomes.

EXAMPLE : AI driven Autonomic operations Optimization of Production Schedule I t can analyse thousands of Production Scenarios and create valid and optimal plans/ schedules that maximizes yield while improving other important production outcomes.

ROI Example

  • 10-20% improvement in OTIF planning and scheduling performance.
  • 25% improvement in customer satisfaction.
  • Reduced Delta between Forecast and Billed Sales.
  • 15% reduction in rolling inventory levels.

Data Needed

  • Historical Production Yield data.
  • Historical Production Schedules used.
  • Order Booked.
  • Forecast.
  • Inventory schedules.

Why Visionbot™?


1.1 Purpose Built AI


State-of-the-art and configurable AI engine built with deep industry expertise.

1.2 Outcome Driven


Committed to creating value with an collaborative outcome-oriented approach.

1.3 Interconnected Decisions


Interconnected decisions enabled through our Visionbot™ AI Cloud platform tailored for consumer businesses.

1.4 Time to Value

Accelerated deployment, scalable architecture, faster time-to-value.

With Visionbot™, decisions & workflows are continuously optimized by real-time, unified AI, process mining and automated visual discovery.

Image: VisionBot Stack

Connect with our experts to understand how companies are using Visionbot™ AI driven Computer Vision to strengthen security, safety and streamline operations. https://visionbot.com/contactus

We welcome Technology Integrators and sector specific VAR’s to be come a Visionbot™ channel partner, and discover the opportunity to offer a cutting-edge AI-powered computer vision solution to your customers. https://visionbot.com/partnering.

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