Parade is a capacity management platform that utilizes AI to automate the load booking process for freight brokerages, enabling teams to double their load coverage per person. By streamlining carrier communication and dynamically pricing freight based on real-time capacity, Parade enhances operational efficiency and increases productivity in the logistics industry.
Funding
$37.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
ISFounders
Product
Problem
Freight brokerages face challenges in efficiently managing capacity, leading to difficulties in load booking, carrier communication, and dynamic freight pricing. This often results in reduced load coverage per person and inefficiencies in the logistics process.
Solution
Parade offers a capacity management platform that leverages AI to automate the load booking process for freight brokerages. The platform streamlines carrier communication, dynamically prices freight based on real-time capacity, and enhances operational efficiency. By automating tasks and providing data-driven insights, Parade enables teams to cover more loads per person, source reliable carriers, build stronger relationships, and price freight confidently. The platform integrates with existing TMS, carrier onboarding, visibility, and rate benchmarking tools to unify the tech stack.
Target Audience
Parade primarily targets freight brokerages seeking to improve operational efficiency, increase load coverage, and strengthen carrier relationships.
Features
- AI-powered automation of the load booking process
- Dynamic freight pricing based on real-time capacity and market trends
- Automated load offers and self-service portals for carriers
- Data-driven CRM for managing carrier relationships
- Integration with TMS, carrier onboarding tools, visibility tools, and rate benchmarks
- Automated load coverage with preferred carriers for recurring lanes
- Real-time capacity management and lane data analysis