Summary

A private client required 3 tasks. First, enterprise operations support; the client needed ongoing minimal support to ensure minimal disruption for on-going enterprise operations. Second, support in existing minor DME CIO; the client needed approved monthly minor development, modernization, and enhancement sprints for existing technology and data assets. Finally, support in 2.0 minor DME; the client required a CIO-approved and 2.0 monthly minor development, modernization, and enhancement sprints for new technology and data assets.

Problem and Solution

The problems are the aforementioned tasks that required Xentity’s project expertise. First, regarding minimal enterprise operations support, Xentity provided ongoing minimal support to ensure minimal disruption for on-going enterprise operations. The team will provide ongoing support to mature the web application and review the mobile application to improve security, bugs, and infrastructure. This includes enterprise infrastructure deployment & documentation, triage and support, enterprise quality assurance support. Next, Xentity provided CIO-approved monthly minor development, modernization, and enhancement sprints for existing technology and data assets. Finally, Xentity provided ongoing minimal support to ensure minimal disruption for on-going enterprise operations.

Outcome and Benefits

Xentity’s efforts helped the client reach production deployments. Also, for the 1.1 NLP release, Xentity helped with the job update function. Namely, Xentity enhanced job screens, and created job edit screen functions. Furthermore, Xentity provided additional enhancements. This included improvements into the PubSub notifications, adjustments to the UI for optimization or feedback from the client, and video tutorials for the client and providers. Finally, Xentity’s ongoing minimal support has involved maintaining a roadmap. From this roadmap, there have been several user stories to help the client in new features in the NLP/AI areas. This increased vocabulary, improved data quality and model tuning, and hardened the solution to make this a world-class unique solution. This not only enabled improved use of NLP/AI for the client, but also allowed the collection of vocabulary to open new channels as a core set of data for additional purposes.