Boosting Security and Efficiency with an AI Chatbot and Admin Tool
The company was seeking to improve operational efficiency while maintaining data security through the development of an internal AI chatbot, SpectrumGPT. In collaboration with cross-functional teams, I played a key role in designing the Admin interface, enabling team leaders to request, customize, and manage AI chatbots.
COmpany:
Spectrum (Charter Communications)
Industry:
Telecom & Mass Media
Project name
SpectrumGPT
Timeframe
APR 2024 - JUN 2024
Scope of work:
Stack:
Results
Measurable Improvements in Workflow
The launch of SpectrumGPT led to meaningful efficiency gains and strong user satisfaction. By streamlining the press release workflow and providing intuitive tools for content generation and management, the platform delivered clear impact for internal teams.
Problem
Let's not expose all our data
AI Chatbots have taken the world by storm. They offer functionality to help businesses drastically improve efficiency and effectiveness. However, there’s a big problem with employees of an enterprise business using ChatGPT, or another third-party chatbot - companies don’t want their secure data to be exposed. That’s why Spectrum is rushing to build their own internal chatbot to empower their stakeholders and improve their bottom line.
Solution
Consumer Chatbot & Admin Interface
Spectrum will build its own Chatbot and Admin tool called SpectrumGPT. This system will allow leaders to request a chatbot for their team, upload documents to be ingested into vector collections, test and configure chat flows, grant access, forecast budgeting, and monitor activity.
My Role and the Team
Two designers, One project
During this project, I collaborated with another designer. My co-worker was in charge of the landing page and end-user experience, while I led the design of the Administration tool. Despite our specific roles, we both had an impact on the designs of each page and feature. Over several weeks, our Scrum team had daily meetings with a Data Science team to develop the AI Chatbot application. Additionally, we interviewed various stakeholders within Spectrum, including members of the Press Release and IT Specialist teams. I dedicated approximately 4 months to working on this project while developing the MVP.
Project summary
From learning about GPT, to loading up a bot for your team
As a design team, my coworker and I collaborated with cross-functional team members, including Software Engineers and Data Scientists, to build an intuitive Chatbot system for Spectrum stakeholders. The product includes a landing page where users can learn more about the application and request a chatbot for their team, a web application for users to interact with their own custom chatbot, and an Admin interface that allows leaders to request a chatbot for their team, upload documents to be ingested into vector collections, test and configure chat flows, grant access, forecast budgeting, and monitor activity.
High-Level Requirements
Setting Up a Chatbot
A key focus area for the product is allowing a product owner or manager to request a custom AI chatbot for their team to be more efficient and effective. This process includes three main steps: Step 1 - Use Case Information: The user creates a use case name, enters their information, and info about their team and the project the use case will help with. The user uploads supporting documentation and selects 1-3 language models to try out. Step 2 - Preview: The user previews the chatbot experience using different LLMs, for example, OpenAI LLM, Linx LLM, and (Fill in LLM name). The user compares the language models. Step 3 - Selection: The user selects the best language model for the use case and submits the chatbot request.
Use Cases
Understanding the Three Key Departments
Leadership identified three use cases which would be our initial focus for teams who could make the best use of a custom chatbot, with the Press Release department being the key focus.
Press Releases
Spectrum's MVP rollout initially targeted press releases as a key use case. Large companies like Spectrum regularly issue press statements concerning new product launches, quarterly earnings, partnerships, and more. Crafting these statements involves repetitive tasks following a specified writing style, formats, and information-sharing formulas. The writing must adhere to proper grammar, spelling, and a corporate tone. Press releases also entail accurately presenting company data and figures, necessitating precise input of large numbers. Due to the somewhat repetitive and formulaic nature of this task, and the demand for precision and proper language, press releases were considered the ideal use case for SpectrumGPT's MVP.
IT Specialist
The role of IT Support Specialists is vital in maintaining Spectrum’s IT infrastructure. They tackle various technical issues, from troubleshooting software problems to handling hardware malfunctions. The chatbot designed for IT Support Specialists offers quick access to technical documentation, step-by-step troubleshooting guides, and support ticket management. By leveraging the chatbot, IT Specialists can address issues more efficiently, minimizing downtime and improving overall system reliability. The chatbot can also assist in identifying common problems, suggesting potential solutions, and automating routine tasks, enabling IT Specialists to focus on more complex issues.
Customer Service
Spectrum’s Customer Service Representatives (CSRs) deal with a high volume of customer inquiries daily, ranging from billing questions to technical support and service requests. The chatbot for customer service automation aims to aid CSRs by providing swift and accurate responses to common questions, managing routine tasks, and routing more complex issues to human agents when necessary. This automation helps reduce response times, enhance customer satisfaction, and free up CSRs to handle more complex customer interactions. Furthermore, the chatbot can furnish CSRs with pertinent information and context about the customer’s history, facilitating more personalized and effective service.
Collaboration
Gelling with the Data Science Team
For several weeks leading up to engineering kickoff for this project, our scrum team was introduced to a team of Data Scientists, who joined our morning standups and other sprint ceremony meetings. This allowed us to form a working relationships and see things from one another’s perspective.
Wireframes
Sketching Screens for Use Cases
We used low-fidelity sketches to validate concepts with leadership. (Include some details - make up something about feedback from stakeholders about the “Use Cases Index” page on what information would be most critical to see in the data table from each index.)Aligning with Engineering for the MVPTo ensure the MVP met all technical requirements, we held regular sync meetings with the engineering team. These sessions were crucial for aligning on the technical feasibility of our designs and making necessary adjustments based on engineering feedback.
This page serves as a landing page stating “Welcome to SpectrumGPT” and a button to request a use case. The page also displays example prompts, a preview of the chatbot, info about the available LLMs, Frequently Asked Questions, and a way to reach out with additional questions.
Design Slideshow
Focus Groups
Recieving feedback
We presented our prototype flows to individual contributors and managers from our key focus departments including: • Press Release • Customer Service • IT Specialists
Usability Testing
Testing Prototype Flows
One-on-one testing sessions with participants were conducted to evaluate user behaviors and prototypes for system improvements. During these sessions, we guided users through various scenarios, observing their interactions with the chatbot and admin tool. This allowed us to identify pain points and gather valuable feedback for refining the user experience. For example, users found the “Use Cases Index” page particularly useful but suggested adding a column for the “Last Updated” date to keep track of recent changes.
