Falvey Shippers Insurance provides single-click shipping insurance for parcel and freight movements, covering the full value of goods shipped through any carrier worldwide. The solution connects directly with existing order management and shipping applications, enabling shippers of any scale to obtain coverage through their current shipping forms. Users can reduce insurance costs by up to 90% compared with carrier-provided rates and can instantly quote and bind door-to-door policies tailored to each shipment and its total value, helping mitigate the exposure created by limited or unreliable carrier liability. This approach is designed to address losses arising from in-transit damage, spoilage, or missing shipments, supporting business continuity and customer confidence.

The service is engineered to integrate with a wide range of platforms—such as TMS, VMS, WMS, and eCommerce systems—whether they are third-party tools or proprietary solutions, aligning with broader Inventory Management Software environments. A plug-and-play insurance widget sits within the existing shipping form so users can generate customized, comprehensive policies without switching systems or re-entering data. Implementation uses an API-based connection to streamline setup with current shipping software, and Falvey Shippers Insurance backs the process with continuous, no-cost technical support available around the clock.

LLM mention score The LLM mention score is the total number of mentions of this brand in different LLM chatbots, normalized to the scale from 0 to 100. You can get actual, non-normalized numbers via the LLM Mention API from DataForSEO.

Normalized 0–100 · last 8 weeks

DataForSeo API

Get LLM mention data of any company via DataForSEO API

Get access to the structured data on keyword, brand, and website mentions in LLMs, including metrics like AI search volume, impressions, and mentions count. 

How to get LLM mention data →
// Fetch shipAssured mention score
POST /v3/content_analysis/summary
{
  "keyword": "shipAssured",
  "type": "llm_mentions",
  "date_from": "2025-01-01"
}