The ecosystem approach adopted by Tradeleaf focuses on open IoT and AI protocols to enhance connectivity, increase efficiency, and improve the transparency of the supply chain, creating a new digital network to facilitate and optimise trade finance. Tradeleaf acts as a systems integrator, uniting numerous solutions and services under a single platform supported by a complex architecture and effective technical practices.
Over the past several decades, digital technology, from Al to loT and Blockchain, has permeated supply chains, global trade, and finance. Some work to collect and deliver data, while others analyse and interpret it. Others still provide the infrastructure that allows this communication to occur. Based on this, the technologies described below do not function in isolation but rather synergize within the context of their mutually complementary profiles.
A set of ecosystem participants: traders, liquidity providers, and service partners, who utilise services and modules from app and services layers. Users form connections with other ecosystem participants and generate data to be processed and securely stored on the network, protocol, and infrastructure layers.
This layer holds the Tradeleaf Platform’s marketplaces, including the Deal Marketplace, Trade Finance Marketplace, Crypto Lending Marketplace, and Solutions & Services Panel. Each has focused functionality that coalesces into comprehensive systems responsible for different activities on the platform.
This is the most complex layer that consists of dozens of independent or connected microservices either provided by service and software providers or developed by Tradeleaf. The services layer helps clients to receive any ministration directly and almost instantly.
Network & Protocol Layer
This layer is responsible for service layer data management and availability. It consists of a public blockchain network (Polygon, Fantom, Binance Smart Chain) and a private blockchain network, the Hyper Ledger Fabric, which contains parts of a centralised and decentralised database and stores data. Digitisation and automation of work processes are carried out through AI/ML modules responsible for efficient routing across the platform. The loT management system refers to processes related to the provisioning and authentication, configuration, support, monitoring, and diagnostics of connected devices operating as part of an loT environment in the Tradeleaf ecosystem.
This layer is responsible for all critical data management, connectivity, and availability functions. Cloud computing and cloud processing are necessary to connect different data sets throughout the supply chain while providing sufficient flexibility to support other connectivity options. Data connections are the essential factors on all levels of the infrastructure.
New technologies such as blockchain, artificial intelligence, and cloud computing are changing how trade finance, payments, and settlements are organised. The digitalisation of trade finance brings opportunities and technology into the world of trade to reduce reliance on paper and manual processes and improve customer interactions.
Tradeleaf s network and protocol layer use a technology stack ideal for facilitating trade finance operations, ultimately providing the best user experience.
Tradeleaf uses two sets of blockchains: permissionless public and secure private. A public blockchain utilises various protocols and smart contracts on Crypto Lending Marketplace. In a public blockchain network, everyone has access, can see the ledger, and take part in a consensus process.
The Tradeleaf Platform uses cryptography methods to improve security in the public blockchain network and ensure the integrity and authenticity of transactions by utilising hash functions and private digital signatures. Signatures play a dual role, additionally serving as identification due to the properties of public and private key pairs. Thus, this digital signature provides reliable ownership control.
A smart contract is a self-executing contract with the terms of the agreement between participants written into lines of code. Smart contracts in the Tradeleaf Platform provide several technical and legal functions. These contracts automatically perform tasks after a triggering event involving multiple parties happens.
With DeFi on the Tradeleaf platform, consumers can do most of the things banks support, such as earn interest, borrow, lend, buy insurance, provide liquidity, and trade assets. DeFi uses smart contracts to turn money into a programmable and interoperable protocol.
A cross-chain bridge is a protocol that allows different blockchains to cooperate. Bridges connect separate blockchains, allowing users to transfer assets, tokens, smart contract information, and other forms of data between networks. Cross-chain technology in the Tradeleaf Platform helps achieve interoperability by enabling data exchange between blockchain projects or external systems. Such data exchanges can increase the flexibility of the digital ledger design, overcome performance issues, and improve overall security.
A private blockchain is a closed ecosystem closed to public participation. Participants must obtain permission from a centralised authority before using a private blockchain. Using the private Hyper Ledger Fabric network on the Tradeleaf Platform provides key technical advantages, mainly the lowest costs and higher speed than a public blockchain platform can offer.
Tradeleaf’s Additional Solutions and Services and Deal Marketplace obtain data integrity, provenance transparency, privacy, and security through the Hyperledger Fabric private blockchain network, which provides the best balance between traditional web technologies and public blockchains.
Data privacy and access control in the Hyperledger Fabric private blockchain network diverges into five aspects. The first aspect is to divide the network into channels, where each channel represents a subset of participants who have the right to view the data for the chaincodes deployed on that channel. The second is to limit the input data for the chaincode using visibility settings. The third is to hash or encrypt the data before calling the chaincode. The fourth is to restrict data access to specific roles in the organisation by building access control into chaincode logic. The fifth is to encrypt registry data at rest using file system encryption on the peer device, also encrypting data in transit.
A database is an organised collection of structured information or data, typically stored electronically in a computer system. The database complies with the Hyperledger Fabric and has the following functions: privacy protection, indexing, key-value stores, and interacting with chaincodes.
The state database describes the current state of all assets in the blockchain network. When the asset status changes, additional records are added with the new version number. In the context of the Hyperledger Fabric, the state database is called the world state, and various ecosystem inputs can create, update, and delete states, so the world state can change frequently.
Under the proposed network architecture, every organisation involved in the supply chain is part of one channel. Hyperledger Fabric networks are structured so that each track links to a single ledger and is only accessible to peers within the same channel.
The transparency of events along the supply chain is a significant enabler of faster payment, improved financing, increased efficiency, reduced risk of fraud, and lower costs. Exchanging information related to these events in a distributed ledger facilitates trigger events that need to take place for goods to arrive at their final destination and for suppliers to receive payment.
The Internet of Things (loT) is a network of physical objects with sensors, software, and other technologies. Trackers are equipped with these technologies that allow them to process and exchange data with other connected entities and systems in the Tradeleaf Platform. These connected devices work with automated systems to gather analysable data to assist with tasks or investigate how to improve a process.
In the Tradeleaf Platform, applications for accounting and monitoring processes of loT devices, providing software updates, and general administration of the device lifecycle are given significant importance. The software is mainly responsible for managing chaincode oracles, thus providing a robust data-entry solution. Thus, events reported by such loT oracles can be used as triggers to release funds, mitigating the dissonance between sellers who want payment before shipment and buyers who wish to ship before payment.
The Tradeleaf Platform uses artificial intelligence(AI) to optimise decision-making efficiency and speed. While big data analytics collects valuable data for people to use in decision-making, artificial intelligence can process this data further and make actual decisions. The ability of Al-based programs to analyse and understand data has vast implications for funding processes.
Natural Language Processing
Tradeleaf uses machine capabilities combined with Al models to work with text and analyse data on the platform. Techniques using NLP in the Tradeleaf Platform contribute to a financial infrastructure that can make informed real-time decisions. The OCR technology digitises printed texts to become electronically editable, searched and used in digital ecosystem processes.
Automated AI Scoring
Implementing artificial intelligence in the Tradeleaf Platform creates competitive advantages for financial companies, improving their efficiency by reducing costs, increasing productivity, and improving the quality of services and products offered to consumers.
Automated AI scoring unlocks insights to improve financing flow by analysing the creditworthiness of customers with limited credit histories. A better outcome for credit scoring could help shift the focus towards reasonable risk, increasing MSME access to trade finance.
In the Tradeleaf Platform, Al monitoring is an integral element in data analytics and provides comprehensive solutions for the dynamic resolution of organisational issues, risk management mechanisms, data classification, and fraud prevention. It offers an opportunity to evaluate unstructured data about risky behaviour in the organisation's activities. Additionally, Al algorithms identify patterns of behaviour associated with past incidents and use them as predictors of risk.
Artificial intelligence systems significantly reduce the load on such processes and fraud threats.
Machine Learning and Big Data
The Tradeleaf platforms ML models use big data to automatically learn and improve predictability and performance using experience and data without human programming. ML analyses large amounts of data from various sources, generating real-time predictive models that promptly address risks.
The main feature of big data analytics in the Tradeleaf Platform is advanced techniques against extensive and diverse data sets that include unstructured data from different sources to uncover hidden patterns, correlations and other insights. Data-driven insights reduce the human errors involved in loan management when developing a risk profile of customers requesting financing and credit scoring.
An application programming interface (API) is a software intermediary that effectively allows two programs to interact with each other. APIs act as bridges between trade tech and third-party applications or programs used by their customers.
Through the transparency enabled by blockchain and the connectivity that APIs provide, the Tradeleaf Platform offers access to seamless real-time payments and financing solutions for platform-facilitated trade flows.