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Bots in robotic process automation

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Bots in robotic process automation

  1. 1. Bots in Robotic Process Automation byCarlosToxtli
  2. 2. Experience
  3. 3. Human-Computer Interaction
  4. 4. The research side of life ...
  5. 5. Let's start with Machine Learning
  6. 6. All that we need is data!
  7. 7. Feed the machine learning model with the data ...
  8. 8. Training the model ...
  9. 9. Now we have a model to predict new data!
  10. 10. But an AI model is a single piece of a solution
  11. 11. Robotic Process Automation is the missing link ...
  12. 12. Robotic Process Automation = Software Automation
  13. 13. Bots (agents) are the building blocks of RPA Bots simulate & understand human interactions such as: - Vision - Audio - Text - Interfaces interaction - Location
  14. 14. Tools are reactive, Bots are proactive & reactive You use an app when you need it A bot contacts you when it needs you.
  15. 15. RPA + AI = Intelligent Automation / Cognitive RPA
  16. 16. RPA for AI Bots for Data collection Bots for monitoring the input channels Bots for training the AI model
  17. 17. Data come to me ... But getting the right amount of data in the format that we need is not always easy ...
  18. 18. Web crawlers / Spiders / Scrapers
  19. 19. Different sources
  20. 20. Scraping platforms
  21. 21. Data cleaning ...
  22. 22. Then we can train a model in an old fashion way
  23. 23. Or with RPA automate the machine learning process ...
  24. 24. AutoML platforms
  25. 25. Then we need to have an interface for the model Bots are implemented in channels or applications that supports bidirectional communication such as Notifications, Webhooks, or Endpoints.
  26. 26. Bots on messaging channels
  27. 27. Messaging bot platforms
  28. 28. RPAFrameworks
  29. 29. Examples of RPA that implements Bots & AI
  30. 30. FineBot - RPA (chatbot,crawler) only Parking Speed limit ... 8:15pm 🤖: Hey David there is a fine charged to your car. The concept was illegal parked. 8:15pm 🤖: David I’m sorry to let you know that your son got a ticket. The concept was illegal parked 🤖 8:15pm David: My plate is: ABC123
  31. 31. BobbaBot - RPA (chatbot) + NLP 8:00am Mark: Hey bob about, today I gonna get a taro tea 8:00am 🤖: Got it! 8:15pm Lupe: Bob please bring me a Matcha 8:15am 🤖: Got it! 8:45pm Alice: Today I want a Honey Dew tea 8:00am 🤖: Got it! 9:00am 🤖: Hey Mike this is the Ford’s order for today: Honey dew, Matcha, and Taro 9:15am 🤖: Hey group, your beverages are at the reception. 8:00am 9:00am
  32. 32. ApprovalBot - RPA (email) + AI The bot gets a document approval request for 3 people The bot sends the document approval request and tracks its completion Every time that a document is accepted or rejected the bot learns the criteria The bot learns the times of each actor and their criteria to give suggestions in the future Suggestion
  33. 33. TaskBot - RPA (voice) + NLP From: luis@... To: carlos@..: john@... Cc: taskbot@... Hey taskbot, Please remind Carlos yo send the proposal by Friday and Luis to send the signed contract. Task management tool John Carlos Luis 🤖
  34. 34. MATT - RPA (crawler) + AI Student sends an assignment A bot recruits experts on Linkedin The assignment is sent to the most relevant and available expert The experts evaluate the assignments and provide feedback
  35. 35. The bot monitors the sensors (physical or visual) and failure alerts (even audio) Failure Predictor Bot - RPA (sensors) + AI Every time that a failure happens, the bot learns from the previous sensors information The bot is able to prevent failures when early symptoms are raising. 🤖 The bot sends a preventive message to operators when there is a potential failure.
  36. 36. Security - Liveness test (RPA + Machine Vision) The system requires to ensure that it’s you and activate the verification bot The bot starts a video call or request the use of the webcam The bot process the video on real time and verifies that the person matches with an ID and is not a photo or a phone screen The bot retrieves the decision to the system.
  37. 37. ImporterBot - RPA + ML - All autonomous The bot searches for trending products on Chinese marketplaces The bot stores the found products and assigns a competitive price for the local marketplace The bot publishes the products in the marketplace (MercadoLibre) The bot waits for purchased products The bot confirms the payment The bot purchase the product in the Chinese store and set the customer shipping address The bot track the package and update customer of any delay The bot gives feedback to the customer and reminds the customer to give feedback
  38. 38. And many many more ...
  39. 39. Lessons learned ● Automated recruitment systems are effective over work channels (Linkedin) ● Automation helps to scaling solutions. ● Social friction is reduced in mediated communication. ● Even that all the selling workflow can be automated. The vendors and the delivery services should be properly selected in advance. ● Mitigation strategies must be always set on any AI solution.
  40. 40. How to go from the idea to the implementation? ● Structure your idea as an autonomous system that can act whenever it is needed without necessarily having human intervention. ● Diagram a workflow of your solution. BPM diagrams are commonly used. ● Identify what processes requires simulated interaction and processes can predict values from data. ● Implement the elements by using RPA frameworks and AutoML. ● Test and deploy using continuous integration.
  41. 41. Tutorials for getting started ● Collection of curated RPA content http://bit.ly/awesome-rpa ● Collection of curated AI content http://bit.ly/awesome-ai ● Main AI technologies explained http://bit.ly/siselai ● UiPath video tutorials https://www.uipath.com/developers/video-tutorials
  42. 42. Conclusions ● AI often relies on RPA to be implemented ● RPA solutions are more useful when these are not only rule based ● Coordinating human teams and orchestrated bots lead to boost productivity
  43. 43. Thanks @ctoxtli carlostoxtli.com