Enterprise AI APIs — Complete Guide
Enterprise AI APIs — Complete Guide: free step-by-step lesson with examples, common mistakes, and interview tips — part of ML.NET Tutorial on Toolliyo Academy.
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ML.NET Tutorial · Lesson 90 of 100
Enterprise AI APIs
Foundations ✓ → Models ✓ → NLP & advanced ✓ → MLOps
MLOps · 4 — APIs & deploy · ~10 min · Module 9: ASP.NET Core AI Integration
What is this?
Enterprise AI APIs add SLA tiers, audit logging, schema validation, and backward-compatible versioning.
Why should you care?
AIPredict enterprise merchants require audit trails and 99.9% uptime on fraud scoring.
See it live — copy this example
Use a .NET console or Web API project with Microsoft.ML. Run dotnet run after pasting.
app.MapPost("/api/v1/fraud/score", async (TxRow tx, PredictionEnginePool<TxRow, FraudPred> pool, IAudit audit, HttpContext ctx) =>
{
var p = pool.Predict(tx);
await audit.LogAsync(ctx.User.Identity!.Name!, tx, p, modelVersion: "v12");
return Results.Ok(new ApiEnvelope<FraudPred>(p, requestId: ctx.TraceIdentifier));
});What happened?
- Envelope responses include requestId for support.
- Audit stores who scored what for compliance.
Practice next
- ApiEnvelope wrapper.
- Audit each predict.
- TraceIdentifier in response.
- SLA tier header routing.
- Deprecate v1 with sunset header.
Remember
Audit trail. Stable envelopes. Versioned routes.
AIPredict enterprise SLA
Bank audits fraud scores for Q2.
Outcome: RequestId traces every prediction row.
Interview prep for this lesson
Practice these questions aloud after reading—each links to a full structured answer.
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