Why this subject deserves an implementation guide
The starting question for this article came from a public Context.dev post titled "Top 12 Data Enrichment Companies to Watch in 2025". Rather than reproduce that article, this guide asks what the same product problem looks like inside MediaHarvester and what can be verified in the running application.
A company record becomes useful when it can be recognized, routed and reviewed without a teammate opening five browser tabs for every account.
The MediaHarvester approach
Retrieve public brand context, attach logo and description fields, classify only with stated confidence and preserve the source domain alongside CRM edits.
The primary surface for this workflow is `GET /v1/brand/retrieve`. It can be tried from the API playground and integrated through the local API key, SDK, CLI or MCP layer.
Workflow map
A realistic application scenario
A sales operations team receives a CSV of work emails and wants account records that are readable before routing leads.
The workflow begins with a narrowly scoped public or authorized source, records the endpoint output and makes the result reviewable before it becomes visible to users or informs an automated decision.
Try the capability
GET /v1/brand/retrieve Local API key:mh-localhost-dev-key
GET /v1/brand/retrieve?domain=web-tasarimci.comImplementation choices that matter
Classification is a routing hint, not an unquestionable truth. Keep manual correction possible, especially where enrichment affects outreach or prioritization.
This matters because a production feature is judged less by a perfect demo result than by how it behaves when an asset is missing, a source changes, a response is cached or a request is not allowed.
How to measure whether it works
Track populated fields, accepted classifications, corrections, account routing speed and the quality of follow-up workflows.
The app should retain enough source and request metadata to debug poor results while applying appropriate retention and access policies for customer data.
A responsible next step
Run the included endpoint against a website you control or are authorized to process, inspect the response in Visual and JSON modes, then decide which fields deserve automation and which deserve human approval.
MediaHarvester deliberately treats blocked, verification-required, login-required, robots-disallowed and permission-required outcomes as information, not obstacles to be bypassed.
FAQ
Questions teams ask before implementing this workflow
What does this company intelligence workflow return?
It uses GET /v1/brand/retrieve and related MediaHarvester surfaces to return structured context together with metadata appropriate to the workflow.
Can I test this locally?
Yes. Run the local service at http://127.0.0.1:8013 and send X-API-Key: mh-localhost-dev-key to protected API routes.
Does it work with private or blocked pages?
The platform is designed for publicly accessible or authorized sources. Verification, login, permission and robots restrictions are reported rather than bypassed.
Can this be automated?
The same API surfaces are available through CLI, Python and TypeScript SDKs, MCP tools and starter no-code integration templates.
How do I keep the result current?
Use cache freshness controls such as maxAgeMs where exposed, and schedule refreshes in a production worker only as frequently as the business case needs.