Jev as a Pre-Filter in the Ticket Workflow: Fewer Model Calls, Fewer False Alarms
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n8n — Advanced Topics

Deep dives accompanying the "Getting Started with n8n" series: individual topics that go beyond the basics, from LLM memory to advanced workflow patterns.

The main series “Getting Started with n8n” goes from the first container to a production pipeline. These Advanced Topics pick out individual subjects and go deeper than the introduction allows. Each piece stands on its own but ties back to a concrete point in the main series.

  1. 1

    What an Agent Remembers: LLM Memory between Context Window and Knowledge Graph

    Agent memory is an architecture problem, not a toggle. An ordered overview: the cognitive memory functions, why the context window is not memory, RAG through GraphRAG with their real costs, and where n8n hits its native limits.
    27. Jun 2026
  2. 2

    Jev as a Pre-Filter in the Ticket Workflow: Fewer Model Calls, Fewer False Alarms

    Jev pre-classifies tickets in the n8n workflow, and the local language model only decides when Jev is unsure. Getting there took labels of my own, a corrected priority matrix and a new prompt. Plus a comparison with eight cloud models and the OpenRouter Auto Router, and the cost of 1,000 tickets a day.
    26. Sep 2026

Getting Started with n8n

A series on n8n as a self-hosted workflow and agent platform — from the first container to a production-ready pipeline with AI classification and SAP integration.
  1. 0

    Why n8n, why now — Prologue to the Getting-Started Series

    SAP has taken a strategic stake in n8n and embedded it in Joule Studio. Mercedes-Benz is rolling out the platform globally. A prologue to the n8n getting-started series.
    18. May 2026
  2. 1

    n8n in Overview — Architecture, Item Model, and Demo Repo

    What n8n actually is under the hood: editor, execution engine, task runners, workflows as JSON. Plus the item array as the central data model and where n8n fits in the integration landscape.
    20. May 2026
  3. 2

    Self-Hosting with Docker Compose — n8n, Postgres, and Caddy

    Self-hosting n8n in a production-grade setup: Docker Compose, Postgres instead of SQLite, Caddy with auto-HTTPS, persistent volumes, and the environment variables that actually matter.
    21. May 2026
  4. 3

    Test Data, Because Real Data Is Off the Table

    Why a real ticket dataset has no place in a public repo, and how a hybrid generator using local models and Claude produces realistic test data with a reproducible distribution.
    22. May 2026
  5. 4

    Nodes, Expressions, and the First Workflow Without AI

    Building a rule-based ticket classifier in n8n: the item model in practice, writing expressions correctly, choosing between Set and Code nodes — and where the classifier predictably fails.
    26. May 2026
  6. 5

    Webhooks, HTTP, and Credentials — the Production Entrance

    How an n8n workflow gets an authenticated webhook endpoint, how credentials are stored securely, and how classifier logic is extracted into a sub-workflow.
    27. May 2026
  7. 6

    AI Classification Without the Cloud — the Ticket Workflow Gets a Brain

    How an n8n workflow classifies tickets with a local language model: structured output, two backends without a cloud key, deterministic language detection, and a benchmark that exposes its own weakness.
    1. Jun 2026
  8. 7

    When the Workflow Learns to Fail — Error Handling and Observability in n8n

    The AI classifier runs, but what happens when the model goes down? A global error workflow with a Telegram alert, an observability stack of Prometheus, Loki and Grafana, and a silent fallback that wants to be made visible.
    8. Jun 2026
  9. 8

    One Entry Point, Two Classifiers — Merging the AI Pipeline into the Live Path

    Until now two separate paths ran side by side: the rule-based ingest and the AI classification. This article merges them into one pipeline, makes classification a swappable stage, and positions the rule-based classifier as a deliberate fallback behind the model.
    9. Jun 2026
  10. 9

    Two Models, One Entry Point — Round-Robin and Failover over Local AI Backends

    A single AI backend degrades to the rule-based emergency exit on failure. This article builds real redundancy from two local models: round-robin in normal operation, automatic failover on a single outage, rule-based only when both are down.
    10. Jun 2026
  11. 10

    n8n Meets SAP — the Bridge over OData and HTTP

    The pipeline now enriches its tickets with master data from a SAP backend. This article shows the OData binding over HTTP, SAP's own error format, graceful degradation on an unknown customer, and where AIF stays complementary.
    13. Jun 2026
  12. 11

    n8n in Queue Mode — Main, Worker and Redis

    Operation goes production-ready. This article moves the single-process instance to queue mode: main accepts webhooks and enqueues executions in Redis, workers run them. With worker scaling, queue metrics, a production checklist, and a note on what queue mode does not do.
    15. Jun 2026
  13. 12

    n8n or SAP Integration — Not an Either-Or

    Eleven articles covered what n8n can do. This one places where it does not belong: against SAP Cloud Integration with its EAI heritage and the Edge Integration Cell with its data boundary. With a decision tree instead of a tool takedown.
    15. Jun 2026
  14. 13

    n8n Authenticates Against SAP BTP — OAuth Against a CAP Service

    The series finale: n8n binds to its own service on SAP BTP with a real OAuth flow. Client Credentials against the xsuaa token endpoint, a CAP service as a SAP-native stand-in, the n8n OAuth2 credential, and a workflow that enriches a ticket with a case ID from BTP.
    19. Jun 2026