Sifty uses AI to analyze parcel data and automatically flag merchandise descriptions that violate customs regulations. This technology significantly reduces manual inspection time, allowing brokers to process shipment data up to ten times faster. The platform ensures compliance while increasing processing throughput with high accuracy.
Funding
$500K 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.
Founders
Product
Problem
Customs brokers face challenges in efficiently processing a high volume of international shipments while maintaining accuracy and compliance with regulations. Manually inspecting each parcel is time-consuming and prone to errors, leading to delays and increased operational costs. Identifying potentially problematic shipments that require closer inspection is difficult and can result in bottlenecks.
Solution
Sifty provides an AI-powered platform that automates the classification and triage of international shipments, enabling customs brokers to process parcels faster and more accurately. The platform leverages machine learning models trained on over 10 million transactions verified by authorities and customers to identify patterns and inconsistencies in shipment data. By automatically flagging potentially problematic parcels, Sifty allows customs teams to focus their efforts on high-risk items, reducing processing time and improving compliance. The software integrates with existing systems via API, allowing teams to increase efficiency without additional hires.
Target Audience
Sifty primarily targets customs brokers and international trade and logistics companies seeking to improve the efficiency and accuracy of their customs clearance processes.
Features
- AI-powered classification and triage of international shipments
- Machine learning models trained on a large dataset of verified transactions
- Automatic flagging of potentially problematic parcels based on regulatory compliance and data inconsistencies
- Integration with existing systems via API
- Customizable subscription packages based on processing needs
- Continuous feedback loop to improve system efficiency and keep recommendations up to date with current regulations