8 industries | 32 pipelines | 5 architecture patterns

Magister Solutions:
32 Production-Ready AI Pipelines

Battle-tested across 8 industries. Deploy in minutes, not months.

Industry Solutions

Every Industry. One Platform.

Each solution ships with pre-built pipelines, sample data, and live demos you can deploy today.

Architecture Patterns

5 Proven Pipeline Patterns

Common architecture patterns used across all 32 pipelines. Each compiles to a distributed in-memory DAG.

Simple Classification

LLM Router with multi-way branching. A single LLM call classifies input and routes to different sinks based on the result.

Source LLM Router Sink A / B / C

Used in: Support routing, clinical triage, news categorization

Two-Stage AI

Threshold-based second LLM for cost optimization. Only uncertain results get escalated to a more expensive model.

Source LLM 1 IF <0.8 LLM 2

Used in: Fraud detection, content moderation, KYC screening

RAG Pattern

Dual-pipeline architecture: an ingest pipeline embeds documents into pgvector, a query pipeline retrieves and augments LLM context.

Docs Embed pgvector LLM

Used in: Knowledge bases, FAQ, clinical trial search, legal RAG

Streaming Aggregation

Filter, aggregate in tumbling windows, apply threshold logic, then trigger AI analysis on anomalous windows.

Stream Filter Aggregate IF AI

Used in: Sentiment dashboard, log anomaly, trade surveillance

Agentic Reasoning

LLM Agent with ReAct loops. The pipeline orchestrates tool calls, observation steps, and iterative reasoning until the agent reaches a conclusion. Each loop iteration is a streaming pipeline stage, not an HTTP roundtrip.

Input Agent Tool Call Observe Reason Answer

Used in: Product recommendations, agentic research, supplier risk assessment

Live Environment

All Demos Run Live

Every pipeline on this page is deployed and running. Try them yourself — no signup, no sandbox, no waiting.

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Pick an industry, choose a pipeline, and deploy it to your infrastructure. Our team will help you customize and scale.