Intelligent Automations for Retail
How can Python automations optimize retail operations?
Reduction of Automation Failures
With the rapid and efficient development of RPAs in Python, LG Brasil invested in new automations with bot management and BotCity's governance. The ability to monitor and manage bot operations in real time prevented failures and ensured consistent automation delivery. This saved 15,000 hours of manual tasks over 2 years—Check out the full case.
Improved Performance and Speed
Havan, a national retail leader, accelerated critical processes by 6 times using Python RPA, significantly increasing its development capacity and automation speed. With the emergence of governance challenges, Havan decided to implement BotCity's orchestration tool for code-based automations. Check out the case.
Integration with Legacy Systems
Python-based RPA automation can be applied in ERP (Enterprise Resource Planning) system management, enabling process automation without the need to replace existing infrastructure, reducing costs, and minimizing operational disruptions.
Benefits of BotCity Centralized Governance in Intelligent Automations in Python for Retail
Flexibility and Elimination of Lock-in:
With Python and BotCity, your company eliminates the risk of vendor lock-in, allowing integration with any system, without being tied to low-code tool licensing contracts.
Operational Scalability without Increasing Costs:
Using Python and open technologies, your IT team can scale operations without increasing costs by leveraging a vast ecosystem of libraries and services.
Advanced Software Engineering Practices:
With Python automation, your team can adopt advanced software engineering practices such as code management and CI/CD. This facilitates the reuse of solutions, ensures compliance with industry standards, and accelerates quality development.
Centralized Governance at Enterprise Level:
BotCity Orchestrator provides a robust platform to centrally manage, monitor, and scale automations, with advanced features like execution scheduling, version control, real-time log viewing, and custom alerts.
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"Adopting Python for our operations was intended to give us greater freedom in advanced research. Python’s extensive libraries, particularly those focused on artificial intelligence, offer capabilities that are more challenging to achieve with other tools.”
Luis Arantes Filho
DX Coordinator at LG Electronics
The low-code platform no longer met our needs. We lacked flexibility and couldn’t surpass a certain performance threshold.
Carlos Alexandre
Product Owner at Havan Labs
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