Shipsi is raising $2,000,000 with a minimum reservation of $10,000. Numbers displayed include non-binding reservations before investors are verified, signed, or closed.
We supercharge on-demand delivery for brands and retailers by aggregating next-generation logistics providers and supply enterprise-grade support and tooling.
Website LaunchedNovember, 2017
Two Beta ImplementationsOctober, 2017
Former Uber Executive Joined Shipsi TeamAugust, 2017
First E-commerce PartnershipJuly, 2017
First RevenueJune, 2017
Public Launch to Complete $2M in Convertible NotesMay, 2017
First Transportation Partnership & Transaction ProcessedApril, 2017
Restoration Hardware signed Letter of IntentMarch, 2017
Development CommencedFebruary, 2017
Raised $350K Through Friends & FamilyJanuary, 2017
Shipsi ConceptualizedDecember, 2016
It's Simple: We generate revenue from every brand, retailer, order, and partner: • Brands & Retailers: Implementation fee, setup fee, and fee per transaction • Logistics & Transportation Partners: 50% of freight cost • Strategic Partners: Revenue share model
We allow traditional e-commerce companies to compete with Amazon by aggregating some of the biggest on-demand players in the industry. Today's consumers are seeking instant gratification and immediate convenience. Brick and mortar stores continue to decline, e-commerce is on the rise and every brand/retailer is desperately trying to figure out how to stay alive in today's turbulent retail market.
The on-demand market is relatively new but there are substantial resources available for this market, this report from Accenture is indicative of where the market is going https://www.dropbox.com/s/m2724dbhnaolw1i/Accenture-Strategy-On-Demand-In-Demand.pdf?dl=0 we fundimentially believe that all logistics will be on demand and just in time because of the huge cost and efficency savings.
This is true of traditional logistics but not the case in on-demand, just like Uber was able to leapfrog ahead of the thousands of taxi companies that had been established for decades, we can leapfrog ahead of the incumbents because they cannot innovate at the same pace.
Keep in mind we are a technology platform, we never actually touch a package, our software allows any type of provider in the logistics network become an on-service provider. Just like Uber has no drivers, nor do we, we enable any logistics provider whether it be a driver, broker, warehouse, plane, train or automobile to participate in on-demand logistics market and we make money by taking a small cut of the total volume of business as well as being able to sell ancillary products like insurance and payment facilitation to the industry.
We believe because software patents are very hard to enforce our strongest protections will lie in the algorithms and artificial intelligence technology we build which we do not want to expose our proprietary methods to the industry via patent publishing. This technology is behind the scenes and cannot be replicated without access to our code giving us a high level of protection. However we do have provisional process patents that we will submit once we have the data to back them up.
Right now when you want to send something you have to arrange in advance to get the shipper to pick it up. This means you have to keep more inventory, plan ahead for the volume and make sure that you have relationships in place to meet that volume. With on-demand you get everything "Just in time" which is a far more efficient and lower cost of dealing with logistics. In fact supermarkets were the pioneers of Just In Time logistics, we are just bringing it to everybody else. The ultimate expression of this is that for example a retail shop does not need a stock room, because the moment they sell out of their last pair of jeans, and a whole new batch get delivered at that moment. It sounds complex, and it is which is why we use artificial intelligence.
Artificial Intelligence(AI) also known as Machine Learning is the next revolution in computing. AI allows computers to take in millions of pieces of information in real time and find and learn from patterns within that data, just like the human brain.