Total Supply


Token Distribution

  • Admin 5% 50,000,000
  • Legal 1% 10,000,000
  • Liquidity 5% 50,000,000
  • Advisor / Partners 12% 120,000,000
  • Marketing 6% 60,000,000
  • Token Sale 28% 280,000,000
  • Strategic Acquisitions 5% 50,000,000
  • R&D 17% 170,000,000
  • Ecosystem 21% 210,000,000
Initial Market Cap


Total Fund



Initial Supply



Tokens Sold



Token Fundraiser

Round Seed Private Public Total
Sale% 62.5% 16% 21.5% 100%
Tokens 175,000,000 45,000,000 60,000,000 280,000,000
Price .015 .020 .025
USD Raised 2,625,000 900,000 1,500,000 5,025,000
14,000,000 5,400,000 12,000,000 31,400,000

Token Fundraiser

Round Seed Private Public Total
Sale% 62.5% 16% 21.5% 100%
Tokens 175,000,000 45,000,000 60,000,000 280,000,000
Price .015 .020 0.25
USD Raised 2,625,000 900,000 1,500,000 5,025,000
14,000,000 5,400,000 60,000,000 79,40,000
Percentage Allocation Percentage Unlocked at TGE Vesting
1% Legal 0% Released only when necessary
5% Strategic Acquisitions 0% Released only when necessary
17% Research/Development 0% 6 month lock with 5% released monthly thereafter
6% Marketing 0% 12 month lock with 5% released monthly thereafter
5% Liquidity 0% Released only when necessary
21% Ecosystem 0% Locked for 6 months
5% Admin 0% Locked for 6 months
7% Advisors/Partners 0% 2 months cliff with 10% release, locked for 6 months and released weekly for 2 months
5.0% IDO Partner 0% 1 month cliff followed by 1 month vesting
17.50% Seed 8% 8% at TGE, rest released after a 6 month cliff
4.5% Private 12% 12% at TGE followed by a 6 month release.
6% Public 20% 20% at TGE, rest released weekly for 4 months

Current Implementation
& Tokenomics will utilize Algorand’s ASC1 to keep track of order details. We will achieve this by storing all order details of a day, made to, stored into one IPFS file. The hash of the IPFS file is stored in another IPFS file. The second IPFS file acts as an index file for finding the order details of a particular day. This second IPFS file has the first one’s hashes, mapped based on dates. Every time there’s an update to the second IPFS file, ie, end of each day, when the entire order details of a new day are added to one IPFS file and its hash generated and stored in the second file, the hash of the second IPFS file changes. Each of the changed hashes is stored inside our ASC1, as a global variable. This system of storage allows us to query the order details of any particular day. will utilize the Algorand Standard Assets protocol to launch BUY tokens on Algorand. ASA requires setting up a few immutable asset parameters during the creation of a new asset.

  • 1. Creator – (current address of the ASA creator on Algorand mainnet)
  • 2. Asset Name – BUY TOKEN
  • 3. Unit Name – BUY
  • 4. Total -1 BILLION (maximum supply)
  • 5. Decimals – 6 (divisible up to 6 decimal places, 0.000001 being the smallest unit of BUY)

In this section, we describe several aspects of the’s BUY token

Phase 1

  • Build IOS and Android App for Driver Network (Completed)
  • Complete monitoring center for last mile delivery (Completed)
  • Complete all GPS tracking and driver notifications. (Completed)
  • Complete partnerships with driver’s centers (Completed)
  • Complete block chain wallets for businesses for payment processing (Completed)

BUY Token Current Uses:

  • Used for staking tokens in order for Microdistribution centers to participate
  • Used for staking tokens in order for Delivery operators to participate
  • Used as rewards when a user recommends to another service, and the former receives rewards in the form of tokens
  • As a form of payment in the network specifically for shipping
  • As a form of payment to Microdistribution centers and Delivery operators for providing a service

Phase 2

The first e-commerce protocol that allows consumers to buy direct from manufacturers, wholesalers and distributors. It’s the next generation Decentralized E-Commerce platform that harness the power of distributed ledger technology along with innovations in Bulk Pricing. Real-time Logistics, E-Commerce and Cryptocurrency to use the token in the ecosystem for payment of products.

  • Decentralized Distribution to compete with Amazon and Walmart’s reach leveraging existing latent capacity of garage space similar to the Airbnb model.
  • storefront technology that is superior to $17 Billion Shopify.
  • Direct to Consumer Technology that provides Buyers to group purchases together to meet Minimum Order Quantities to gain economies of scale—with advantages of Costco or Alibaba.
  • Built-in BUY Tokens Cryptocurrency with incentive schemes for Node operators to help scale the network
  • Delivery Network to match local delivery at the last mile with Uber-like capabilities for anyone to deliver goods.
  • Real-time Logistics Data: Manufacturers, Businesses, and Consumers will have seamless access to real-time shipping data to optimize drop shipping costs provided by a permissionless, public blockchain—more transparent than FedEx.
  • We combine the best of blockchains to offer customers a digital ledger that offers a fraud-proof solution and auto-verifies transactions for a tamper-proof, secure, immutable audit trail.
  • Integrated back office e-commerce processing technology.(

Federated Byzantine Agreement

The primary consensus algorithm used is the Federated Byzantine Agreement, as exemplified in the payment of dividends or staking by nodes. For node staking, the node operator will be a Microdistribution center or a Delivery operator, and they will be allowed to store or carry goods commensurate with their stakes. In other words, if Microdistribution center A stakes 50,000 tokens but Microdistribution center B only stakes 10000 tokens, then the former will be allowed to store 5x (five times) the value of merchandise compared with the latter

When packages are delivered to a buyer, if the package requires a delivery signature, that signature would be captured over the mobile application for Delivery Partners. This Proof signature can be verified by the Buyer in a dispute over a mobile app. Without a signature when one is required, a transaction will not be approved.

Metcalfe’s Law

The network with its Direct-to-Consumer approach in being able to aggregate purchases is akin to growing a network of users. The larger the population of buyers, the better the chances of fulfilling an MOQ deal opportunity. But how does one model the value of the network?

For this, we can invoke Metcalfe’s Law,11 which states that the value of a network is proportional to the square of the number of connected users of the system (n2).

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