Chat with Your .NET Assembly and Generate Working Code

AI Assembly Chat starts with static analysis, not guesswork. When you upload a DLL, EXE, or NuGet package, .NET reflection walks its public surface — namespaces, classes, interfaces, enums, methods, properties, and any XML doc comments attached to them — while internal and private members are excluded. This gives the AI ground truth about your specific assembly version instead of relying on generic training knowledge of the package.

That extracted metadata, along with inferred usage patterns, is embedded and indexed for semantic search (RAG), so a question like "how do I serialize an object with this library" retrieves the actual relevant methods and their real signatures rather than a plausible-sounding guess. This indexing step is what lets answers stay accurate even for internal, uncommon, or recently changed APIs that a general-purpose model would never have seen.

Retrieved signatures and doc comments then ground the AI's response: working C#/F# code samples with correct using statements and async patterns, plain-language explanations of what a type or method does, or on-demand SVG class diagrams and PlantUML sequence diagrams showing how the real API pieces connect. Nothing you upload is stored beyond your session or used to train models.