The Problem: Currently, the Fabric Ideas portal contains thousands of entries. Users often find it difficult to search through existing ideas before posting. This leads to: Fragmented Voting: 500 votes for a feature might be spread across 10 different similar posts, making the feature look less popular than it actually is. Increased Moderation Overhead: Microsoft team members must spend manual hours merging ideas or closing duplicates. Search Fatigue: Users often give up searching and just post a new idea, further cluttering the database. The Proposed Solution: Integrate an Azure OpenAI-backed Chat Assistant directly into the "Submit a New Idea" workflow. How it would work: Real-time Analysis: As a user types their "Idea Title" and "Description," the AI analyzes the intent of the request in the background. Intervention & Suggestion: Before the user hits "Submit," a side panel or pop-up appears saying: "It looks like you want to improve [X]. Here are 3 existing ideas that match your request. Would you like to vote for these instead?" Semantic Search: Unlike a basic keyword search, the bot would use semantic embedding to understand that "Allowing Python in Data Factory" and "Support for .py scripts in ADF" are the same request. Draft Refinement: If the idea is truly unique, the bot could suggest ways to improve the description (e.g., "Would you like to add a use case to make this idea clearer for the product team?") to ensure high-quality submissions. Benefits to Microsoft: Cleaner Data: A significantly lower volume of duplicate entries. Accurate Signal: Consolidated voting gives the product team a much clearer picture of what the community actually wants. Cost Efficiency: Reduces the manual labor required by community managers to prune and organize the portal. Benefits to the Community: Instant Gratification: Instead of waiting for a new post to be approved/noticed, the user can immediately put their weight behind a post that already has 200 votes, bringing it closer to the "Planned" status. Better Quality: Higher quality, well-explained ideas are more likely to be implemented. @Miguel_Myers @rui_romano
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