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AI Blog, 2023 Blog, Blog, BOTs Blog, Featured

Relevance Lab is an Automation specialist company providing BOTs and Platforms for Business Processes, Applications, and Infrastructure. Our solutions leverage leading RPA (Robotic Process Automation) tools like UiPath, Automation Anywhere & Blue Prism. We provide re-usable templates for common use cases across Finance & Accounting, HR, IT, and Sales process automation.

By leveraging our robotic process automation services, our clients have realized:

  • 60-80% cost savings
  • 2-3x increase in process speed
  • 35-50% increase in employee productivity
  • Upto 30% FTE (Full Time Equivalent Headcount Reduction)

The biggest challenge in adoption of RPA for our customers primarily comes in identifying “where to start” dilemma. To help identify “what can be automated” we have designed the following guidelines to help with initial use cases for implementation:

  • High frequency and volume workflows
  • High complexity processes
  • High error prone and human task quality related areas
  • Domains with compliance needs with benefits of automated outcomes

Using these broad guidelines across a set of corporate functions we have commonly encountered the following use cases for RPA.

Finance & Accounting Automation

  • Stock Price Update
  • Purchase Order Process
  • Reconciliation Process
  • Payment Process
  • Financial and Loan Origination Process
  • Lease Accounting Process
  • Journal Process
  • Inventory Control Process
  • Error Audit Process
  • Invoice Process

Human Resources (HR) Automation

  • New Hire Onboarding Process
  • Data Approval Process
  • The Policy Processing (TPP)
  • Off-boarding Process
  • Legacy (AS/400) Process
  • Document Handling
  • Employee/HR/IT Process
  • User and Workspace- Employee/Contractor Offboarding
  • Back to Office (COVID) workflow automation and compliances

Infrastructure (IT) Management Automation

  • Distribution List Process
  • User Account Re-conciliation Process
  • Mailbox Automation & Reconciliation Process
  • User Migration & Access Control Verification Process
  • Logs Capture

Sales Automation

  • Contract Data Extraction
  • Sales Reporting
  • Sales Reconciliation Process
  • Material Edits Adjustments

With our comprehensive suite of RPA services, we have not only helped businesses adopt, but also maximize their investments in RPA.

The figure below explains the RPA Top Use Cases solved by Relevance Lab.



RL RPA Offerings
RPA Consulting/Assessment: RPA consulting and assessment is the process of evaluating organization’s processes and identifying opportunities for automation. It is essential for ensuring that RPA implementation is successful.

RPA Implementation: RPA implementation is the process of deploying and using RPA bots to automate processes. It is essential for realizing the benefits of RPA.

Automation Design: Automation design is the process of designing and implementing automation solutions. It involves understanding the business needs, identifying the processes that are suitable for automation, and designing and implementing the automation solutions.

Automation Support: Automation support is the process of providing support to users of automation solutions. It involves providing help with troubleshooting problems, resolving issues, and providing training on how to use the automation solutions.

The figure below explains our core offerings.



Relevance Lab “Automation-First” RPA Platform Architecture
Applications under Robotic Process Execution
RPA is well suited for enterprises and enterprise applications like ERP solutions (For example, SAP, Siebel, or massive data processing or records processing applications like Mainframes). Most of these applications are data-centric and also data-intensive with loads and loads of setup and repetitive process activities.

RPA Tools

  • It has the ability to automate any type of application in any environment.
  • Develop software robots that understand recordings, configuring, and enhancing these with programming logic.
  • Build reusable components which can further be applied to multiple robots, ensuring modularity and faster development and at the same time easier maintenance.

RPA Platforms
Ability to develop meaningful analytics about robots and their execution statistics.

RPA BOT Workbench
RPA execution infrastructure can sometimes be a bank of parallel physical or virtual lab machines, which can be controlled based on usage patterns. Scaling up or down the number of machines in parallel to achieve the task of automation can also be done, and this can be left unattended for as long as you like (as this requires no further human interaction or intervention).

The figure below explains the Relevance Lab “Automation-First” RPA Platform Architecture.



How to get started for new customers?

  • Reach out to Relevance Lab (write to marketing@relevancelab.com) for a quick discussion and demonstration of the standard solution
  • We will study the processes and help in identifying repetitive and manual tasks
  • Engage in creation of POC while selecting the right RPA Tool
  • Customers with standard needs can get started with a new setup in 4-6 weeks
  • Relevance Lab will also provide on-going support and managed services


Summary
Relevance Lab Automation at a Glance

  • RL has been Automation Specialist since 2016 (7+ Years).
  • Implemented 30+ successful customer automation projects covering RPA lifecycle.
  • Globally has 60+ RPA specialists with 150+ certifications.
  • Automated over 100+ processes, which includes customized solutions for industries like across Healthcare, BFSI, Retail and Technology Services & Manufacturing.

References
CoE Manager|Automation Anywhere
Build Your Robotic Process Automation Center of Excellence (uipath.com)



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2023 Blog, Blog, BOTs Blog, Featured, RLCatalyst Blog

With growing interest & investments in new concepts like Automation and Artificial Intelligence, the common dilemma for enterprises is how to scale these for significant impacts to their relevant context. It is easy to do a small proof of concept but much harder to make broader impacts across the landscape of Hybrid Infrastructure, Applications and Service Delivery models. Even more complex is Organizational Change Management for underlying processes, culture and “Way of Working”. There is no “Silver bullet” or “cookie-cutter” approach that can give radical changes, but it requires an investment in a roadmap of changes across People, Process and Technology. RLCatalyst solution from Relevance Lab provides an Open Architecture approach to interconnect various systems, applications, and processes like the “Enterprise Service Bus” model.

What is Intelligent Automation?
The key building blocks of automation depend on the concept of BOTs. So, what are BOTs?


  • BOTs are automation codes managed by ASB orchestration
    • Infrastructure creation, updation, deletion
    • Application deployment lifecycle
    • Operational services, tasks, and workflows – Check, Act, Sensors
    • Interacting with Cloud and On-prem systems with integration adapters in a secure and auditable manner
    • Targeting any repetitive Operations tasks managed by humans that are frequent, complex (time-consuming), security/compliance related

  • What are types of BOTs?
    • Templates – CloudFormation, Terraform, Azure Resource Models, Service Catalog
    • Lambda functions, Scripts (PowerShell/python/shell scripts)
    • Chef/Puppet/Ansible configuration tools – Playbooks, Cookbooks, etc.
    • API Functions (local and remote invocation capability)
    • Workflows and state management
    • UIBOTs (with UiPath, etc.) and un-assisted non-UI BOTs
    • Custom orchestration layer with integration to Self-Service Portals and API Invocation
    • Governance BOTs with guardrails – preventive and corrective

  • What do BOTs have?
    • Infra as a code stored in source code configuration (GitHub, etc.)
    • Separation of Logic and Data
    • Managed Lifecycle (BOTs Manager and BOTs Executors) for lifecycle support and error handling
    • Intelligent Orchestration – Task, workflow, decisioning, AI/ML


To deploy BOTs across the enterprise and benefit from more sophisticated automation leveraging AI (Artificial Intelligence), RLCatalyst provides a prescriptive path to maturity as explained in the figure below.


ASB Approach
An Open- Architecture approach to interconnect various systems, applications, and processes similar to the “Enterprise Service Bus” model. This innovative approach of “software-defined” models, extendable meta-data for configurations, and a hybrid architecture takes into consideration modern distributed security needs. This ASB model helps to drive “Touchless Automation” with pre-built components and rapid adoption by existing enterprises.

To support a flexible deployment model that integrates with current SAAS (Software as a Service) based ITSM Platforms allows Automation to be managed securely inside Cloud or On-Premise data centers. The architecture supports a hybrid approach with multi-tenant components along with secure per instance-based BOT servers managing local security credentials. This comprehensive approach helps to scale Automation from silos to enterprise-wide benefits of human effort savings, faster velocity, better compliance and learning models for BOT efficiency improvements.


RLCatalyst provides solutions for enterprises to create their version of an Open Architecture based AIOps Platform that can integrate with their existing landscape and provide a roadmap for maturity.


  • RLCatalyst Command Centre “Integrates” with different monitoring solutions to create an Observe capability
  • RLCatalyst ServiceOne “Integrates” with ITSM solutions (ServiceNow and Freshdesk) for the Engage functionality
  • RLCatalyst BOTs Engine “Provides” a mature solution to “Design, Run, Orchestrate & Insights” for Act functionality

Relevance Lab is working closely with leading enterprises from different verticals of Digital Learning, Health Sciences & Financial Asset Management in creating a common “Open Platform” that helps bring Automation-First approach and a maturity model to incrementally make Automation more “Intelligent”.

For more information feel free to contact marketing@relevancelab.com

References
Get Started with Building Your Automation Factory for Cloud
Intelligent Automation For User And Workspace Onboarding
Intelligent Automation with AS/400 based Legacy Systems support using UiPath
RLCatalyst BOTs Service Management connector for ServiceNow



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2023 Blog, Blog, BOTs Blog, DevOps Blog, Featured

With growing interest & investments in new concepts like Automation and Artificial Intelligence, the common dilemma for enterprises is how to scale these for significant impacts to their relevant context. It is easy to do a small proof of concept but much harder to make broader impacts across the landscape of Hybrid Infrastructure, Applications and Service Delivery models. Even more complex is Organizational Change Management for underlying processes, culture and “Way of Working”. There is no “Silver bullet” or “cookie-cutter” approach that can give radical changes but it requires an investment in a roadmap of changes across People, Process and Technology.


Relevance Lab has been working closely with leading enterprises from different verticals of Digital Learning, Health Sciences & Financial Asset Management on creating a common “Open Platform” that helps bring Automation-First approach and a maturity model to incrementally make Automation more “Intelligent”.



Relevance Lab offers RLCatalyst – An AIOps platform driven by Intelligent Automation paves way for a faster and seamless Digital Transformation Journey. RLCatalyst Product is focused on driving “Intelligent” AUTOMATION.


AUTOMATION is the core functionality including:
  • DevOps Automation targeting Developer & Operations use cases
  • TechOps Automation targeting IT Support & Operations use cases
  • ServiceOps Automation targeting ServiceDesk & Operations use cases
  • SecOps Automation targeting Security, Compliance & Operations use cases
  • BusinessOps Automation targeting RPA, Applications/Data & Operations use cases)

Driving Automation to be more effective and efficient with “Intelligence” is the key goal and driven by a maturity model.
“Intelligence” based Maturity model for Automation
Level-1: Automation of tasks normally assisting users
Level-2: Integrated Automation focused on Process & Workflows replacing humans
Level-3: Automation leveraging existing Data & Context to drive decisions in more complex processes leveraging Analytics
Level-4: Autonomous & Cognitive techniques using Artificial Intelligence for Automation



RLCatalyst Building Blocks for AIOps

AIOps Platforms need to have common building blocks for “OBSERVE – ENGAGE – ACT” functionality. As enterprises expand their Automation coverage across DevOps, TechOps, ServiceOps, SecurityOps, BusinessOps there is need for all three stages to Observe (with Sensors), Engage (Workflows), Act (Automation & Remediation).


RLCatalyst provides solutions for enterprises to create their version of an Open Architecture based AIOps Platform that can integrate with their existing landscape and provide a roadmap for maturity.


  • RLCatalyst Command Centre “Integrates” with different monitoring solutions to create an Observe capability
  • RLCatalyst ServiceOne “Integrates” with ITSM solutions (ServiceNow and Freshdesk) for the Engage functionality
  • RLCatalyst BOTS Engine “Provides” a mature solution to “Design, Run, Orchestrate & Insights” for Act functionality


For more information feel free to contact marketing@relevancelab.com


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2021 Blog, Blog, BOTs Blog, Featured

While helping our customers with the right way to use the cloud using an Automation-First approach, the primary focus from Relevance Lab is to enable significant automation (achieved 70%+ for large customers) of day-to-day tasks with benefits on the speed of delivery, quality improvements, and cost reduction. Large customers have complex organizational structures with different groups focussing on infrastructure automation, application deployment automation, and service delivery automation. In many cases, there is a missing common architecture in planning, building, and running a proper end-to-end automation program. To help enterprises adopt an Automation-First approach for cloud adoption covering all three aspects of infrastructure, applications, and service delivery, we help create a blueprint for an Automation Factory.

In this blog, we are sharing our approach for large customers with a complex landscape of infrastructure and applications. The focus of this blog is more on application deployment automation with custom and COTS (commercial off-the-shelf) products in Cloud.

Some of the most typical asks by customers with all their workloads in AWS Cloud is captured below:


  • Separation of roles between common infrastructure teams and multiple business units managing their own application needs
  • Infrastructure teams provide base AMI with CloudFormation stacks to provide basic OS-level compute workloads to application groups, who manage their own deployments
  • Application groups deal with a set of custom Java + .NET applications and COTS products, including Oracle Fusion Middleware stacks
  • Application groups manage the complete lifecycle of deployment and support in production environments
  • Application deployments are about 20% containerized and 80% direct installations in hybrid scenarios with legacy codebases
  • Different set of tools are used along with homegrown custom scripts
  • Primary pain points are to automate application and product (COTS) build and deploy lifecycle across different environments and upgrades
  • The solution is expected to leverage DevOps maturity and automation-led standardization for speed and flexibility
  • Need guidance on the choice of Automation Factory model between mutable vs. immutable designs

Key requirements from application groups are shared below based on the snapshot of products for which there is a need for automated installation and scalability at run-time. The shift needs to happen from “handcrafting” product installations to automated and easy deployment, preferably with immutable infrastructure.


Standard Products COTS Products (High Priority) COTS Products (Good to have)
Weblogic Oracle E-Business Suite (Financial Portal) Cisco UCM
Tomcat 7, 8, & 9 OBIEE Kofax
Apache Oracle Discoverer IBM Business Rules Engine
IIS 10 Oracle Siebel CRM Aspect
Oracle 19 Microsoft SQL Server Reporting Service Avaya
SQL Server Oracle Fusion AS/400 Apps
MS SQL SAP Enterprise Adobe AEM


Relevance Lab Approach for Hyperautomation with RLCatalyst and BOTs
Our teams have implemented 50+ engagements across customers and created a mature automation framework to help re-use and speed up the need for an Automation Factory using RLCatalyst BOTs and RLCatalyst Cloud Portals.

The figure below explains the RLCatalyst solutions for hyperautomation leveraging the Automation Service Bus (ASB) framework that allows easy integration with existing customer tools and cloud environments.


The key building block of automation depends on the concept of BOTs. So what are BOTs?


  • BOTs are automation codes managed by Automation Service Bus orchestration
    • Infrastructure creation, updation, deletion
    • Application deployment lifecycle
    • Operational services, tasks, and workflows – Check, Act, Sensors
    • Interacting with Cloud and On-prem systems with integration adapters in a secure and auditable manner
    • Targeting any repetitive Operations tasks managed by humans – frequently, complex (time-consuming), security/compliance related
  • What are types of BOTs?
    • Templates – CloudFormation, Terraform, Azure Resource Models, Service Catalog
    • Lambda functions, Scripts (PowerShell/python/shell scripts)
    • Chef/Puppet/Ansible configuration tools – Playbooks, Cookbooks, etc.
    • API Functions (local and remote invocation capability)
    • Workflows and state management
    • UIBOTs (with UiPath, etc.) and un-assisted non-UI BOTs
    • Custom orchestration layer with integration to Self-Service Portals and API Invocation
    • Governance BOTs with guardrails – preventive and corrective
  • What do BOTs have?
    • Infra as a code stored in source code configuration (GitHub, etc.)
    • Separation of Logic and Data
    • Managed Lifecycle (BOTs Manager and BOTs Executors) for lifecycle support and error handling
    • Intelligent Orchestration – Task, workflow, decisioning, AI/ML

Proposed Solution to Customers
There are different approaches to achieving end-to-end automation, and the right solution depends on a proper assessment of the context of customer needs. Relevance Lab follows a consultative approach that helps do a proper assessment of customer needs, priorities, and business goals to create the right foundation and suggest a maturity model for an Automation Factory. Also, different engagement models are offered to customers covering the entire phase of the Plan-Build-Run lifecycle of automation initiatives, including organization design and change management.

The following table helps plan the right approach and maturity model to be adopted for BOTs targeting different levels of complexity for automation.


BOT Complexity Functionality Coverage Leveraging Relevance Lab Products and Solutions
Level-1 Standard Cloud Resources Provisioning in a secure, multi-account covering compute, storage and data EC2 Linux, EC2 Win, S3 Buckets, RDS, SageMaker, ALB, EMR, VPC, etc. with AWS Service Catalog AWS Console and ITSM Portals RLCatalyst Cloud Portal, BOTs Server CI/CD Pipelines with BOTs APIs
Level-2 Standard Applications deployment covering Middleware, Databases, Open Source Applications requiring single node setup. Single Node COTS setups can also be included though more complex Tomcat, Apache, MySQL, NGINX – common Middleware and Database Stacks Portal, CI/CD Pipeline, CLI Variants:
– Option-1 AMI Based (Preferred model for Immutable design)
– Option- 2 Docker Based
– Option- 3 Chef/Ansible Post Provision App Install & Configure (Mutable Design)
BUILD Phase – Covering Plan, Build, Test, Publish Lifecycle
CONSUME Phase – Production Deploy & Upgrade Lifecycle
Level-3 Multi-tier Applications – 2-Tier, 3-Tier, N-Tier with Web + App + DB, etc. combinations Required a combination of Infra, Apps, Post provision configurations, and orchestration. Complex Infra with ALB, PaaS Service Integrations Orchestration engine and service discovery/registry Docker and Kubernetes clusters
Level-4 Complex Business Apps – ERP, Oracle EBS, COTS, HPC Clusters – not supporting standard Catalog Items. Complex workflows with integration to multiple Third-Party systems UI or System Driven Custom Orchestration Flows and workflow modules Event-driven and state management Post provisioning complex integrations Pre-built BOTs Library

Leveraging a combination of Relevance Lab products and solutions, we provide a mature Automation Factory blueprint to our customers, as shown below.


The above solution is built leveraging best practices from AWS Well-Architected framework and bringing in a combination of AWS tools and other third-party solutions like HashiCorp, Ansible, Docker, Kubernetes, etc. The key building blocks of the Automation Factory cover the following tools and concepts:


  • AWS AMI Builder Factory and Golden AMI concept
  • HashiCorp Packer Scripts
  • OS and Hardening with Ansible
  • Vulnerability Assessment and Patch Management
  • AWS Inspector, AWS Parameter Store, AMI Catalog publishing, Multi-Account AWS Best Practices
  • AWS Service Catalog, Multi-Account Governance, Master and Consumption accounts
  • Self-Service Cloud Portals with guard-rails and automated fulfilment
  • CI/CD Pipelines for non-user assisted workflows using RLCatalyst BOTs, Terraform Templates, Jenkins, Docker, and Kubernetes
  • Monitoring and diagnostics with Observability tools like RLCatalyst Command Center
  • Ongoing Governance, Cost Management, Lifecycle Management, Blue-Green Deployments, and Container Management
  • Cloud Accounts, VPC Automation, AWS Control Tower, AWS Management, and Governance Lens Automation

Summary
The journey to adopting an Automation-First approach requires a strong foundation that our Automation Factory solution offers, saving at least 6 months of in-house efforts and about US$250K worth of savings for large customers annually. The BOTs deployed can scale up to provide productivity gains of 4-5 people full-time employees with other benefits of better fulfillment SLAs, quality, and compliance gains. In the case of COTS deployments, especially with Oracle stacks, our BOTs have reduced the time of deployments from a few weeks to a few hours.

To know more about how can we help your automation journey, feel free to contact marketing@relevancelab.com.

Reference Links
Considerations for AWS AMI Factory Design
AWS Well-Architected Best Practices
ASB – A New Approach for Intelligent and Touchless Automation



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2021 Blog, Blog, BOTs Blog, Featured

In large enterprises with complex systems, covering new generation cloud-based platforms while continuing with stable legacy back-end infrastructure usually results in high-friction points at integration layers. These incompatible systems can also slow down enterprise automation efforts to free up humans and have BOTs take over repetitive tasks. Now with RLCatalyst BOTs Server and leveraging common platforms of ServiceNow and UiPath, we provide an intelligent and scalable solution that can also cover legacy infrastructure like AS/400 with terminal interfaces. These applications are commonly found in the supply chain, logistics, warehousing enterprise domains supporting needs for temporary/flexi-staff onboarding & offboarding needs based on the volume of transactions in industries that see spikes in demand across special events powering the need for more automation first solutions.

Integration of a cloud-based ticketing system with a terminal-based system would always require a support engineer, especially with labor-intensive industries. This is true for any legacy system that does not provide an external API for integration. There are diverse issues that occur slowing down business without compromising on security and governance aspects related to such workflows.

With the lack of a stable API system to interface with the AS/400 legacy system, we decided to rely on BOTs simulating the same User behavior as humans dealing with terminal interfaces. RLCatalyst BOTs was extensively used as an IT Automation solutioning platform for ServiceNow, and the same concept was extended to interact with Terminal interfaces commonly used in Robotic Process Automation (RPA) use cases with UiPath. RLCatalyst acts as in “Automation Service Bus” and manages the integration between ServiceNow ITSM platform and UiPath Terminal Interface engine. The solution is extendable and can be used to solve other common problems especially bringing integration between IT and business systems.



Using UiPath to automate processes in legacy systems
Leveraging the capabilities of UiPath to automate terminal-based legacy systems, RLCatalyst interfaces with the service portal to get all the required information to help UiPath’s UiRobot to execute steps defined in the workflow. RLCatalyst’s BOT framework would provide the necessary tools to run/schedule BOT’s with governance, audit trails functionality.

Case Study – Onboarding an AS400 system user
The legacy AS400 system’s user onboarding process used to be multi-staged, with each stage representing a server with its ACL tables. A common profile name would be the link between the servers and, in some cases, independent logins required. A process definition document is the only governing document that helps a CS executive complete the onboarding process.

The design used to automate the process was:

  • Build individual workflows for each stage in the User interaction processes using UiPath.
  • Build an RLCatalyst BOT which:
    • Refers to a template that includes a reference to the stages to run based on the type of user that needs to be onboarded.
    • Based on the template, it would maintain a document of profile names allotted.
    • Validates the profile availability (this helps onboarding outside the automation)
    • Executes the UiPath workflow for each stage in the sequence defined in the template.
    • Once the execution is complete, a summary of the execution with user login details is sent back to the ITSM system.
    • Logs for each stage are maintained for analysis and error corrections.
  • Build the Service Portal approval workflow, which would finally create a task for the automation process for fulfillment.
    • The service portal form captures all the necessary information for onboarding a new user.
    • Based on the account template selected that depicts a work department, a template reference is captured and included in the submitted form.
    • The service portal is used by the SOX compliance team to trace approval and provisioning details.
    • The process trail becomes critical during off-boarding to confirm, access revocation has occurred without delay.

Advantages of Using UI Automation Over Standard API

  • Some of the AS400 servers used for Invoicing/Billing are over 20 years old, and the processes are as old as the servers themselves. The challenge multiplies when the application code is only understood by a small set of IT professionals.
  • UI automation eliminates system testing costs, since it just mimics a user. All user flows would have already been tested.
  • The time taken to build an end-to-end automation would be significantly lesser compared to getting a highly demanding IT professional building the API interface to get it automated.
  • Total automation investment would also significantly be reduced, and ROI’s would be quicker.

Getting Started
Based on our previous experience in integrating and automating processes, our pre-built libraries and BOTs should provide a head start to your automation needs. The framework would ensure that it meets all the necessary security and compliance needs.

For more details, please feel free to reach out to marketing@relevancelab.com.



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