AI Technologies
Baseline AI Integrated Workflows
Make your operations more contemporary, give direction to your AI strategy for tangible operational productivity gains!
RPA Business Processing
With a combination of Optical Character Recognition (OCR) and Robotic Process Automation (RPA), organizations with high-volume operations can leverage on integration of different technologies to enhance their processing capabilities. Companies, with such integration, can generally deploy solutions which complete utilization of people, assets, and resources for unprecedented gains in productivity. In general, while OCR is not completely accurate in all conditions, as extraction depends on the quality of documents, with formatting and structure, processes can be added to improve overall accuracy and operational outcome.
Chatbot Operations
Companies seeking to improve customer-interfacing outcomes can leverage on technologies that empower their customers in making key choices in their affiliation journey. Convention in general research suggests that the most sustainable sales cycles are those which provide people with agency and choices during their patronage. Technologies such as Chatbots, while they might not entirely leverage on deep-learning technologies, provide customer interfacing channels which are both sustainable and ‘face-less’. While they might appear technology-oriented, they are able to provide immediacy to users in near-realtime resolution scenarios. Chatbots are available across multiple web-based platforms and need to be trained with business conventions for general utility.
AI-Powered Operational Tools
Also known as AIOps (coined by Consulting Firm Gartner), with Big Data, Analytics and emerging technologies such as AI, AI-Powered Operational Tools provide organizations with a focal point where multiple technologies intersect. While not entirely enabling pre-emptive response to specific issues, such technologies enhance visibility through extensive multi-faceted points of intersection which each of these tools aid in. For example, data collection by Big Data repositories provides a larger assessment of unique trends found in your operations. With Analytics, teams can leverage on general visibility tools which classify and identify unique operational patterns for added visualization of traditionally abstract Big Data. With AI, alarms can be set to uniquely identified operational situational trends, so that there can be pre-emptive preventive activities organized around such circumstances. Such tools are not only for DevOps, they are also for operations in scale, as long as the company’s operations leverage on data, of some sort, and operational trends.
Automated Collaborative Tools
While client-based AI powered tools are more established, cloud-based AI solutions are available at the server, where specific requests may be triggered by clients (usually a browser). While Software-as-a-Service (SaaS) and Infrastructure-as-a-Service (IaaS) are relatively contemporary options for businesses to outsource the accessibility factor in their business, companies can easily leverage on more granular application of operationally specific automation tools for very repetitive tasks. Use AI for code-language specific programming projects, create unique AI-powered tools for team creation activities which learn or leverage on active Natural Language Processing (NSP) for situational or business-oriented translation. Collaboration with AI becomes operationally effective as companies evolve to fully utilize deep learning technologies for unique collaboration exercises.