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Custom data acquisition

The data you need is rarely sitting in a catalog.

We map unique sourcing requirements to the right potential data owners, expert channels, and collection pathways—with a focus on practical feasibility and downstream usability.

01 / From spec to source

Sourcing built around what makes an example useful.

A million irrelevant records will not solve a targeted model weakness. We start with the learning signal: what task, behavior, outcome, or distribution is missing?

  • Understand domain, volume, modality, region, and quality constraints
  • Identify prospective owners and validate the likely sourcing route
  • Assess collection methodology and sample feasibility
  • Structure a scoped pilot before expanding the acquisition
Example sourcing brief
“We need multi-step IT support task histories with observable resolutions.”

We would clarify required fields, source authority, confidentiality restrictions, labels, unit economics, and acceptance rules before procurement.

02 / Where we look

Common acquisition targets.

Illustrative categories only. Actual availability is confirmed per request.

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Workflow trajectories

Multi-step sequences linking context, actions, decisions, and observed outcomes.

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Expert demonstrations

Professionally generated domain examples, structured rationales, and task completions.

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Enterprise records

Authorized operational records, documents, conversation histories, and structured process artifacts.

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Multimodal collection

Data programs spanning audio, image, video, language, and mixed modalities.

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Long-tail domains

Specialized workflow contexts where broad public corpora offer limited coverage.

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Acceptance-led pilots

Sample cohorts designed to validate usefulness before larger commitments.

What you can expect first

A practical discovery conversation, initial feasibility questions, and a proposed scope for assessing suppliers and pilot data—not a claim that every dataset already exists in our possession.

Share a data spec
Start a conversation

The hard-to-find dataset might be the right next step.

Bring the problem. We’ll work through what it could take to source the signal you need.

Discuss a data need