For developers building LinkedIn-based enrichment or prospecting tools, Scrapin is an API that returns real-time LinkedIn profile and company data for use in your own product or workflow.

Presence & Market Position

SOV Score

Tracked · below panel floor — earned mentions are accruing toward the next scored window.

Measures earned, engagement-weighted share of voice across the GTM voices panel. Methodology →

Scrapin occupies the LinkedIn-data layer of GTM infrastructure, an API that returns real-time profile and company data for developers building their own enrichment or prospecting tools rather than an end-user lookup tool. The product frames its approach as retrieval over storage, pulling public data at request time instead of serving it from a maintained database, with its compliance framing built around that distinction. Conversation about the brand shows a quieter footprint so far, surfacing more in integration and tooling decisions than in public commentary.

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Business Profile

Scrapin launched in 2020 as a real-time LinkedIn profile and company data API, positioned for developers building enrichment and prospecting tools rather than as an end-user platform, and has stayed a small team as it grew, at seven people. The product has since become part of Reverse Contact, which continues operating the existing API and data pipeline under a new interface while extending into a broader set of B2B lookup tools. The core LinkedIn data product keeps running for existing integrations.

Founded
2020
Employees
7
Status
Independent
Scale stage
Startup
GTM Categories
GTM Developer ToolsData & IntelligenceEnrichment & Signals

Agent Readiness

62B
Agent Readiness
APIMCPSDKCLI

Measures how easily your agents can build on it — API, MCP, CLI, SDK, docs depth. Methodology →

Scrapin's agent-facing surface today is its core API, documented for direct integration into a product or workflow, plus no-code connectors into Zapier, n8n, and Make for teams wiring it into existing automations, and bulk delivery into cloud storage such as S3, GCP, and Snowflake for pipelines that pull data at scale. Data is retrieved in real time rather than served from a stored database, which the product frames as staying current for automated, repeated lookups.

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