> ## Documentation Index
> Fetch the complete documentation index at: https://docs.enterspeed.com/llms.txt
> Use this file to discover all available pages before exploring further.

# What is Speedtrain

> Speedtrain applies AI to structured business data at scale, with humans on the loop and quality checked on every output.

Speedtrain is a governed platform for agentic data enrichment. You point it at structured business data — products, articles, records — describe the content you want generated, and it produces that content for every item, scores each output against your own quality rules, and routes the results to people for approval.

It is built on Enterspeed, so the data you enrich and the content you produce move through the same data supply chain as the rest of your stack.

<Info>
  Speedtrain is for **repeatable content jobs over many records**, not one-off writing. If you need one product description, write it. If you need 40,000 of them in four languages, each one checked against your brand rules, that is a task configuration.
</Info>

## What you do with it

<Columns cols={2}>
  <Card title="Enrich records" icon="wand-magic-sparkles" href="/speedtrain/use-cases">
    Turn sparse product data into descriptions, bullet points, and marketing copy.
  </Card>

  <Card title="Classify and structure" icon="tags" href="/speedtrain/use-cases">
    Assign categories, extract attributes, and normalise messy values.
  </Card>

  <Card title="Translate and localise" icon="language" href="/speedtrain/use-cases">
    Produce the same content per market, with per-language rules.
  </Card>

  <Card title="Read images" icon="image" href="/speedtrain/key-concepts/capabilities">
    Let a vision model describe what is actually in the product photo.
  </Card>
</Columns>

## The governance model

Speedtrain assumes AI output needs checking. Three mechanisms do that work, and they run on every single item:

<Steps>
  <Step title="Quality checks score the output">
    Deterministic rules (schema validation, forbidden terms) run as code in milliseconds. AI rules handle the questions that genuinely need judgment. Each produces a score from 1 to 5 and written feedback. [Quality checks](/speedtrain/key-concepts/quality-checks)
  </Step>

  <Step title="A quality gate aggregates the scores">
    The gate is arithmetic, not an opinion — no model is involved. It decides whether an item can auto-approve or must go to a person. [Quality gates](/speedtrain/key-concepts/quality-gates)
  </Step>

  <Step title="People decide">
    Every item lands in a review session where a human can accept, decline, or send it back for another attempt. Nothing reaches a destination without passing through this. [Review sessions](/speedtrain/key-concepts/review-sessions)
  </Step>
</Steps>

<Tip>
  Humans are **on** the loop, not in it. You are not editing 40,000 descriptions — you are inspecting the ones the gate flagged, and spot-checking the ones it passed.
</Tip>

## Where to go next

<Columns cols={2}>
  <Card title="Data flow" icon="arrow-right-arrow-left" href="/speedtrain/data-flow">
    How data moves between Enterspeed and Speedtrain, in four steps.
  </Card>

  <Card title="How it works" icon="diagram-project" href="/speedtrain/how-it-works">
    The full path from source data to published content.
  </Card>

  <Card title="Getting started" icon="circle-play" href="/speedtrain/getting-started/intro">
    Build and run your first task configuration.
  </Card>

  <Card title="Key concepts" icon="lightbulb-on" href="/speedtrain/key-concepts/overview">
    The vocabulary, one page per concept.
  </Card>
</Columns>