Building Software in 2025: Why .NET + AI Is the Perfect Stack

There's a quiet truth in enterprise AI work that doesn't get talked about much in the JavaScript-heavy AI community: a huge percentage of production AI at scale is running on .NET.

That's not nostalgia. .NET 8 and 9 are genuinely excellent runtimes for AI workloads — and the tooling story has gotten dramatically better in the last 12 months.

The stack we actually ship

For new AI-heavy projects in 2025/2026, our default backend stack is:

• ASP.NET Core 9 for the API layer — minimal APIs, native AOT-compatible.
• Semantic Kernel or direct calls to the Anthropic / OpenAI / Vertex SDKs depending on whether the project needs orchestration primitives.
• Microsoft.Extensions.AI for a unified abstraction over multiple model providers.
• EF Core 9 + PostgreSQL with pgvector for relational data, vector search, and full-text search in one database.
• Aspire for local development and observability — this is the underrated one.

Front-end is whatever fits — Angular for enterprise SPAs, Next.js for marketing-adjacent web apps, Blazor for tightly-coupled internal tools.

Why .NET, specifically, for AI

Three reasons that come up repeatedly:

1. The abstraction layer for LLMs is finally good. Microsoft.Extensions.AI gives you a single IChatClient interface that you can point at OpenAI, Anthropic, Azure OpenAI, Ollama, or Bedrock. Switch providers in one line. We've used this on real projects to A/B test Claude vs GPT-4 in production without changing our application code.

2. Performance is no longer a debate. ASP.NET Core minimal APIs are within a few percent of Go and Rust on most benchmarks. AOT compilation gets you sub-100ms cold starts in containerized environments. For AI workloads where the LLM call dominates the latency budget, the framework overhead just doesn't matter.

3. Enterprise integrations are first-class. Azure AD, SQL Server, Cosmos DB, Service Bus, Event Grid, Key Vault. If your business runs on Microsoft infrastructure — and a lot of Canadian and US businesses do — .NET is the only stack where the integration story isn't a series of third-party adapters.

Where we don't use .NET

We don't use it everywhere. There are clear cases where Python or TypeScript is the right call:

• Heavy data prep and ML training pipelines — Python wins, by a mile. Pandas, Polars, the entire scientific Python ecosystem, GPU support.
• Quick AI agent prototypes — Python with LangChain or the Anthropic SDK gets you to a working demo in an afternoon.
• Marketing / public-facing web sites — Next.js, every time.

The rule of thumb: if the project is going to live for years inside a company's IT estate, .NET. If it's a research prototype or a public marketing site, something else.

The MCP angle

One specific area where .NET has been quietly dominating: MCP servers for enterprise.

The C# MCP SDK is excellent. Combine it with EF Core for type-safe data access, ASP.NET Core for the host, and you've got an audited, scoped, deployable AI tool surface that fits into any existing .NET shop without friction.

We've built MCP servers in three languages now (TypeScript, Python, C#). When the target environment is enterprise — particularly anything touching Azure AD, Office 365, or on-prem SQL Server — C# wins on developer velocity and operational stability.

What this means for you

If you're already a Microsoft shop wondering whether you need to learn a new stack to do "AI properly" — you don't. The .NET ecosystem has caught up. The model providers all have first-class .NET SDKs. The orchestration primitives are mature.

If you're not a Microsoft shop, .NET probably isn't the right call for your AI work. Use Python or TypeScript and don't fight it.

But if you've spent the last decade investing in .NET, there is no longer a meaningful gap between what you can do today and what's possible on the cutting edge of AI tooling. That's a significant change from even 18 months ago.

If you want help getting from "we have .NET" to "we have AI in production on .NET," that's exactly the bridge we build. Get in touch.