AI code intelligence for C# monorepos
GraphSlice turns your C# solution into a semantic code graph and exposes only the context an LLM actually needs to answer a question.
Compiler-grade semantics Delivered over MCP Runs on-premise
A modern C# solution holds millions of relationships between types, methods, namespaces and external packages. Dumping files into a model is slow and expensive. Hoping a vector search retrieves the right ones rarely produces a reliable answer.
GraphSlice builds a semantic code graph of your solution and serves targeted context slices over the Model Context Protocol (MCP). Instead of searching text, your AI assistant queries how the software actually fits together.
Each answer contains only the dependency paths the question needs. That means fewer tokens per query and higher precision in code generation. Costs stay flat as your repository grows.
How it works
GraphSlice fully compiles and understands your C# solution: the same semantic model the compiler uses, not a text approximation.
Compiler output becomes a semantic code graph. Every symbol is connected to the ones it touches, so the graph reflects how your software behaves, not where text happens to appear.
GraphSlice never exposes the whole graph. It serves a context slice: the minimal connected subgraph that answers one question.
Context slices are delivered over MCP. Any MCP-compatible client can request semantic code context. Your repository is never indexed or uploaded.
Why GraphSlice
GraphSlice reads true C# semantics — real types, symbols and references — not the shallow syntax trees generic parsers produce. Queries operate on real symbols and relationships, including external packages and BCL boundaries. No filenames. No grep. No embeddings to drift out of date.
Only the relevant context slice reaches the model. Lower token usage, higher accuracy and faster responses, even on solutions with thousands of types.
Designed from the ground up for LLM workflows. Bring your own MCP client: the graph does the reasoning about structure so the model can reason about intent.
Validated against large, real-world C# codebases, not toy repositories.
The codebase race
An AI agent is asked to locate and understand the
ISocketFactory implementation and its DI registration in the
Jellyfin codebase. Watch what each approach costs in context.
Cost breakdown
≈ — fewer tokens for the same answer
Sovereignty
GraphSlice is built in Belgium by an independent European team for organizations that refuse to compromise on data sovereignty. Your source code is one of your most valuable assets. It should never have to leave your infrastructure to benefit from AI.
Run GraphSlice on-premises, in your private cloud, or in an air-gapped environment. Your repositories never leave your infrastructure, because neither should your intellectual property.
Choose the AI you trust. Connect GraphSlice to your own LLM or MCP client, whether it's self-hosted or based on open-weight models. There's no vendor lock-in, no mandatory cloud service, and no code shared with any model provider you didn't explicitly choose.
Privacy by default. Sovereignty by design. GraphSlice is built for European organizations with strict security, compliance, and data sovereignty requirements, where protecting intellectual property is non-negotiable.
Alpha
GraphSlice is open to a small group of early teams that build large C# applications and want better AI-assisted development. Tell us a little about your codebase and we will be in touch.