Managed search & public web data

LLM datasets.
Your sources.
Your schema.

Search and public web data, collected, structured and kept up to date for your AI pipeline.

Get a dataset quote Explore the data

You define the dataset. We manage collection and refreshes.

Search and public web data flowing through collection, normalization and refresh into maintained structured datasets.

The data layer for your AI workflow

Source referencesCustom schemasScheduled delivery

01 / Inside the dataset

Content with context.
Ready for your pipeline.

Define the content and metadata your application needs. Explore how different public sources can become structured records.

01 / Source content

Public documentation

Workspace setup guide

Organize related projects in a workspace. Assign each project a name and choose the sources it will use. Review the workspace settings before inviting your team.

Source referencehttps://docs.example/guides/workspaces

Document text with a reference back to the page it came from.

02 / Structured record

{
  "source_url": "https://docs.example/guides/workspaces",
  "collected_at": "2026-09-01T09:00:00Z",
  "title": "Workspace setup guide",
  "text": "Organize related projects in a workspace. Assign each project a name and choose the sources it will use."
}

Know the source

Keep a URL alongside the content so your team can trace a record to its origin.

Keep the fields you need

Agree the text, attributes and metadata that belong in your document schema.

Fit your existing workflow

Define file or API delivery around the format your application consumes.

02 / Beyond the first collection

The web changes.
Your dataset can too.

Documentation evolves. Product pages change. Search results move. Plan recurring collection around the sources your AI application depends on.

Choose a collection cadenceSet the frequency around how quickly your sources change.

Keep collection contextAgree the source references and timestamps to retain with each record.

Plan ongoing deliveryDefine how refreshed records reach your team or application.

Collection frequency

DailyEvery 3 daysWeekly

Days since the last collection

Each drop marks a planned collection. Agree the actual timing and coverage for your sources.

03 / Build your dataset

What does your
AI need to know?

Bring your use case. We’ll help define the sources, structure and delivery, then confirm scope and pricing.

Get a dataset quote

A useful starting brief

Sources: Public URLs, search queries and markets
Structure: Content, fields and source metadata
Scale: Estimated records and refresh frequency
Delivery: Your preferred format and destination

We shape the collection around your requirements.

LLM datasets.Your sources.Your schema.

Content with context.Ready for your pipeline.