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GUIDE 02 · INTERMEDIATE · FREE PDF

From tools to systems: your first AI pipeline

Once you've moved past the prompting stage, you need workflows that run without you.

Guide 01 gave you the starting point: four tools, three days, a solid foundation. Now it's time for the next step — moving from individual AI tools to chains that run without you having to trigger them manually.

This guide shows you how to identify which of your workflows are suitable for automation, how to structure them as pipelines, and how to connect AI tools with systems you already have — without becoming dependent on a specific provider.

Everything is tailored for Swedish SMEs: realistic requirements for technical knowledge, concrete examples from Swedish industries, and a clear focus on ROI before you invest a single krona in infrastructure.

42 pages · PDF · Prerequisite: Guide 01 or 3+ months of AI experience · Last updated May 2026

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WHAT YOU WILL LEARN

Eight chapters. One complete system.

Each chapter builds on the one before. You can jump directly to the area you need — but reading in order works best.

  1. 01
    What is an AI pipeline, really?
    Key terms explained. A pipeline is a chain of steps where the output from one step becomes the input for the next — with or without AI in each step. Here, we define exactly what that means.
  2. 02
    Three signs you are ready
    Automation implemented too early costs more than it yields. This chapter shows the three signs indicating you have reached the limit of what individual tools can provide.
  3. 03
    Map your workflows — the 60-minute method
    A structured method to identify which processes are suitable for AI automation. Includes an assessment template and a prioritization matrix.
  4. 04
    Four pipelines that work for Swedish SMEs
    Concrete examples with schemas: email sorting, newsletter production, document analysis, and customer service bots. Each pipeline includes steps, tools, and time estimates.
  5. 05
    Connect existing systems without coding
    Make.com, Zapier, and n8n — how to choose the right one, what they cost, and where they fall short. Includes three ready-made automation templates.
  6. 06
    Error handling — when AI is a weak link in the chain
    AI output is never 100% reliable. This chapter covers how you design pipelines with built-in checkpoints, thresholds, and human review steps.
  7. 07
    GDPR in automated flows
    Automation increases the volume of data being processed. This chapter shows how to design pipelines that respect data minimization and do not create new compliance issues.
  8. 08
    Measure the results — what actually counts
    How you know if your pipeline is working. Three metrics for each pipeline type, how to set a baseline, and what you do when the numbers tell you it's time to change.

A pipeline you build once can run the same job many times.

— Polaris guide 02
PREVIEW — CHAPTER 04

Four pipelines that work

Which pipeline is best depends on the problem. Here are four that come up time and again when I work with Swedish SMEs — because they quickly give results you can measure.

01
Email sorting
Incoming emails → LLM classifies → sorted into folders/CRM → human review of exceptions. Can save a significant part of each working day in companies with high email volume.
02
Newsletter production
RSS/news sources → summary → AI generates drafts → editor approves → scheduled. Takes several hours the first week, much less once the flow is in place.
03
Document analysis and extraction
PDF/Word documents → OCR/parser → LLM extracts key data → exported to Excel/database. Replaces manual data entry.
04
Customer service bot with escalation
Incoming chat → LLM answers known questions → escalates complex issues to a human → logs all interactions. Answers arrive within seconds.
ABOUT THE GUIDE

Daniel Merthen

I run Hrafninn Industries AB and build AI systems for Swedish companies. This guide is written from practical experience of building pipelines that actually hold up in production environments.

Guide 02 is aimed at you if you have already tested AI tools and are ready to take the next step.

Contact Daniel →
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