RPA, ML & AI
The below graphic representation categorizes and stacks-up the various focus areas in “artificial intelligence & automation” space. Broadly, the categorization is a)achieving automation of processes, or b)achieving both automation and intelligence/insights from data replicating human intelligence, and to some extent, human behavior also.
Robotic Process Automation is the technology that allows for humans to configure computer software, or a “robot” to emulate and integrate the actions of a human interacting within digital systems to execute a business process. Or, seen differently, RPA is a generic tool to create specialized agents which can automate clerical tasks. KPMG opines "in the next 10 to 20 years, 47% of jobs will be substituted by automated or robot labor. RPA is a particular type of digitization, and its implementation is absolutely essential to raising a company’s added value in the future".
The value proposition of RPA implementation is generally based on 4 components: cost, quality, speed, efficiency. The same report from KPMG puts labor arbitrage gains from the BPO industry topping off at 30%, but RPA taking it further unto 70%. It is no wonder that the value benefits from RPA deployment are spurring more and and more businesses to embrace this very stable and ‘assured high returns’ technology.
Our approach starts with investigation of identified processes for any improvement/ redesign opportunities before RPA deployment. This is ensures the benefits are multiplied. Our experience includes RPA deployment for back office and customer care processes majorly using using UiPath and blueprism for BFS, Insurance, Healthcare and Manufacturing industries. We follow the frameworks, methodologies and standards set by the product vendors, coupled with our mature Project management practices.
ML & AI
ML & AI: Deloitte Global predicts that in 2018, large and medium-sized enterprises will intensify their use of machine learning. There’s likely to be a 4 fold growth from 2017 to 2020 in ML projects and pilots. International Data Corporation (IDC) forecasts that spending on AI and ML will grow from $12 billion in 2017 to $57.6 billion by 2021. But adoption of ML is still in its early phases majorly because true ML experts are in short supply. Using Java, Python, R, LISP and C++ our consultants have deployed ML & AI in Chatbots, Brand sentiment analysis, Product recommendation, Product demand pattern in specific markets, Machine malfunction prediction, Compliance, Cyber security, Fraud detection, and Disease prediction.
Our engagement models for RPA, ML & AI stretch the gamut from project managed capacity augmentation, to consulting, and Project execution services. What’s even better is that our offshore in-house consultant numbers along with access to specialist affiliates translates into faster deployment capabilities. Talk to us today for how we can help you gain accelerated benefits from use of these technologies.