croutons.

Croutons Docs

Understand the operating layer.

Croutons structures AI activity, visibility signals, workflows, claims, sources, and evidence into reusable records your team can route, govern, measure, and trust.

Core Concepts

The primitives behind Croutons.

Crouton Unit

A structured record created from one messy AI, business, or website signal.

AI Layer Diagnosis

A first-pass map of inference load, routing waste, governance gaps, and operational risk.

AI Visibility Layer

A machine-readable map of crawl paths, schema, feeds, evidence, and answer-ready data.

Evidence Brief

A reusable proof object that connects a claim to source-backed evidence.

Inputs / Outputs

Send messy signals. Get usable records.

Inputs

  • URLs
  • sitemaps
  • schema
  • logs
  • AI outputs
  • workflows
  • policies
  • claims
  • screenshots
  • exports
  • feeds
  • documents

Outputs

  • AI visibility score
  • crawl readiness
  • schema graph
  • evidence briefs
  • risk map
  • workflow gaps
  • citation gaps
  • implementation tickets
  • machine-readable files
  • structured records

First Diagnosis

How the first pass works.

  1. 1

    Send signals

    URLs, logs, docs, exports, workflows, claims, or schema.

  2. 2

    Croutons structures them

    Signals become Crouton Units, Evidence Briefs, or machine-readable records.

  3. 3

    Breaks are mapped

    Crawl waste, inference load, proof gaps, routing risk, and missing structure appear.

  4. 4

    Team gets actions

    Scores, maps, briefs, feeds, and implementation tickets.

Implementation

Start lightweight. Scale into infrastructure.

Diagnosis only

Send sample data and receive a structured report.

Best for
first audit
Output
score, gaps, tickets

Managed layer

Croutons monitors AI activity, evidence, crawl signals, and workflow risk over time.

Best for
ongoing AI operations
Output
monitoring, briefs, visibility maps

Integrated infrastructure

Connect logs, feeds, schema, CMS exports, workflows, and internal systems.

Best for
enterprise teams
Output
structured data layer, feeds, governance records

Machine-Readable Files

Croutons outputs records machines can use.

sitemap.xmlrobots.txtllms.txtai-overview.jsonschema.jsonldpage-index.jsonevidence.jsondecision-objects.jsonservices.jsonproducts.json

These files are examples of machine-readable outputs Croutons can help structure, validate, or generate based on verified business data.

Quick Answers

Common implementation questions.

Do we need production integration first?

No. The first diagnosis can run from sample URLs, logs, schema, workflows, docs, or exports.

Is Croutons an SEO tool?

Not only. It supports AI visibility, evidence, AI operations, workflow risk, and machine-readable business structure.

Does Croutons generate fake claims?

No. Evidence Briefs should only use visible, uploaded, or verified sources.

Does this replace schema?

No. It helps design, audit, connect, and operationalize schema as part of a larger machine-readable layer.

What teams use this?

SEO, AI, product, content, compliance, support, operations, and executive teams.

Can Croutons create implementation tickets?

Yes. Diagnosis outputs can be turned into technical, content, schema, crawl, evidence, or workflow tickets.

Start here

Run your first Croutons diagnosis.

Send URLs, logs, workflows, schema, claims, docs, feeds, or exports. Croutons maps what can be structured, trusted, routed, reused, and improved.

No production integration required for the first diagnosis.