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Data Sources

Data Sources are focused endpoints for single-purpose lookups and enrichments. Instead of running a broad research workflow, you call a specific source operation and get a targeted result back.

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What Data Sources are for

Use Data Sources when you need:

• a specific LinkedIn lookup
• email enrichment or validation
• professional email discovery
• phone enrichment
• Crunchbase company data

These endpoints are ideal for product features that need a narrow, predictable result from a known provider category.

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Current source categories

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LinkedIn

NeuralVerge supports LinkedIn workflows such as:

• profile + email lookup
• profile lookup by domain and full name
• company search
• people search
• company employee search

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Email

Email-focused endpoints include:

• email enrichment
• email validation
• email finder

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Phone

Phone-focused endpoints include:

• phone enrichment
• US phone enrichment

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Company data

Company-focused endpoints include:

• Crunchbase company lookup

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Typical output model

Most Data Source responses include:

• a human summary for UI display
• a machine object with structured provider results
• total_points for usage tracking
• a session_id when the run is tracked asynchronously

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When to choose Data Sources

Choose Data Sources when:

• the lookup target is already known
• you need a narrow endpoint instead of a full workflow
• you want fast provider-specific enrichment
• the output shape should stay focused and predictable

Use AI Research when you need exploration and synthesis across many sources. Use AI Extract when you need schema-based extraction from known content.

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Common product uses

Teams often use Data Sources for:

• lead enrichment
• account research
• contact verification
• company profile resolution
• CRM automation
• outbound workflow support