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Once you have a schema and some assets, you can run analysis. Each document gets processed by your chosen model, and results are stored as structured annotations.

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The Process

1

Select content

Pick individual assets or entire bundles
2

Choose schema

Select which schema to apply
3

Pick model

OpenAI, Anthropic, Google, or local via Ollama
4

Run

Each document gets processed, results stored as structured JSON

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Choosing a Model

Different models have different strengths:
ProviderBest forNotes
OpenAIGeneral extraction, high throughputReliable, fast, good default
AnthropicNuanced analysis, long documentsBetter at complex reasoning
GoogleLarge context windowsGood for lengthy documents
OllamaPrivacy, local processingNo data leaves your machine
For more recent references check: https://artificialanalysis.ai/models
When analysing large collections
  1. Start small - Test on 2-3 documents first
  2. Check outputs - Do they match expectations?
  3. Refine instructions - Tighten schema if needed
  4. Scale up - Run on full collection

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Results

After analysis completes, results appear as annotations on your assets. Each annotation contains the structured data your schema extracted. View results:
  • On the asset - See all annotations for a specific document
  • Fragments - If curated from a table (see curation), you can see the persistent fragments on the asset detail view
  • In dashboards - Aggregate and visualise across the entire run
  • Via export - Download as CSV or JSON for external analysis

Schemas

Define what to extract from documents

Curating Fragments

Promote good extractions to persistent metadata

Dashboards

Visualise results with charts and tables

App Setup

Configure API keys and providers