Search34 Results

The Microsoft 365 integration allows CometAI to work with your Microsoft account services - such as OneDrive and SharePoint - directly inside conversations and assistants. Once connected, you can attach files from OneDrive or SharePoint, and ask CometAI to summarize or generate. CometAI only acts when you request it, and it stays within your existing Microsoft 365 permissions.

This article explains how to access & use the CometAI API Feature. It covers the three types of API keys available in CometAI - Owner Keys, System Keys, and Delegate Keys - including their purpose, when to use each key type, and best practices for selecting the appropriate key based on your use case.

This article guide provides step-by-step instructions on how to securely log in & log out to the CometAI platform using your UT Dallas NetID and password.

Follow-Up Buttons are one-click shortcuts that let you run predefined instructions in a conversation. Instead of retyping common follow-up requests, you can create a button that appears automatically, ready to use.

This article explains what Custom Instructions, Prompt Templates & Follow-Up Buttons are, how they work, and how they differ so you know when to use each one.

Read this article to become familiar with CometAI features.

Learn how to initiate RAG based conversation in CometAI

This article covers the various user-facing CometAI API endpoints available to users. It includes a detailed description of each endpoint, example API requests and URLs, sample request bodies, expected response formats, and guidance on how to test and view responses using Postman. The article also explains the expected data returned by each endpoint, common success and error responses, and provides examples of what a successful API call looks like.

This article provides a comprehensive overview of the advanced configuration features within CometAI. Understanding and utilizing these settings can significantly enhance the model's performance, efficiency, and relevance for academic research, coursework, and development projects.

Comet AI includes a built-in Prompt Optimization tool to help users rewrite vague or unclear prompts into clear, effective instructions. This feature is especially helpful for students, faculty, and staff who want better results without needing to be prompt engineering experts.

This article guides on how users can choose to store conversations either locally on their device or on the cloud for cross-device access

This document provides a high-level comparison of leading language models currently available within the CometAI platform. The models, developed by Anthropic, OpenAI, Mistral, and Meta, are evaluated across performance strengths, cost-efficiency, and best-fit use cases for academic and enterprise environments. This guide is designed to help faculty and staff select the most appropriate model for tasks such as summarization, writing, planning, coding, and visual document interpretation.

This UT Dallas knowledge base article introduces CometAI 3.0, outlining major new features such as API access, SharePoint/OneDrive integration, live web search, over 25 available AI models, custom and group assistants, and enhanced content creation tools for faculty and staff.

This article covers all the updates happening in CometAI for the Year 2026.

This article provides information about CometAI model lifecycle status, outlining upcoming deprecations and End-of-Life (EOL) dates to help users plan for continuity. It includes a master deprecation table with removal dates and recommended successor models, plus notes explaining key lifecycle definitions and implications of using deprecated models.