# Create a company-data quality checklist

Use case · AI agents · Planned API workflow

Canonical page: https://datasdk.ai/use-cases/create-a-company-data-quality-checklist

Plan checks that stop incomplete records from triggering unreliable actions.

## Who this helps

An agent builder needs to know whether a record supports the next task.

## How to use it

1. Define the minimum evidence needed for each action.
2. Validate the domain and distinguish absent fields from negative findings.
3. Return a clear ready-for-review or needs-research result.

## Illustrative example

A proposed agent would request company verification before drafting a brief for an ambiguous domain.

## What to check

The API contract is coming soon; do not assume every field is supplied.

## How Data SDK fits

The full Data SDK API is coming soon. Platform and AI-agent workflows are planning examples. Confirm access, data delivery, usage, branding, and resale terms before building or selling a feature.

These are suggested workflows, not a list of built-in integrations. Use your own approved analytics, CRM, and research process where needed. Matches and fields vary. A company match does not identify a person or prove buying intent.

## Related reading

- [Missing value](https://datasdk.ai/glossary/missing-value): A missing value means a field has no usable information.
- [Schema](https://datasdk.ai/glossary/schema): A schema describes the structure and expected fields of data.
- [Fallback](https://datasdk.ai/glossary/fallback): A fallback is the behavior used when the preferred result is unavailable.
- [Prepare an AI company research brief](https://datasdk.ai/use-cases/prepare-an-ai-company-research-brief): Plan concise briefs tied to a matched company domain.
- [Classify company fit with evidence](https://datasdk.ai/use-cases/classify-company-fit-with-evidence): Plan a reviewable explanation of how a company meets user-defined criteria.
- [Suggest questions for a discovery call](https://datasdk.ai/use-cases/suggest-questions-for-a-discovery-call): Plan questions grounded in the company's business rather than guesses about the visitor.

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