Rokk3r is a holding company that helps startups in leveraging cutting-edge technologies. It works towards investing, integrating and acquiring companies to achieve maximum social impact, value and returns.
They needed to build a blockchain-powered system that would automate the time-consuming process of transferring inter-bank documents at all levels and save the bank's resources.
With this in mind, they approached Deqode requesting a platform that could identify the source of a document and provide a complete audit trail of how the document was verified, thereby ensuring complete provenance tracking.
- 9+ Developers
- 17+ Months Engagement
- Blockchain ecosystem
- Every bank has to be a custodian of the private keys of its employees - so that the employees do not have to worry about the technical aspects of the system. It was only possible within a restricted environment. Rising to the challenge, we used a permissioned blockchain identified using the DLT value analysis framework.
- To increase the multi-level security of private keys for each bank, we created a customized, encryption-based secure digital vault
- To avoid blockchain bloat due to the storage of large amounts of data, we used external storage services to store original documents in an encrypted manner. Only metadata in the form of sha256 hash and audit trail was put on-chain.
- Our experts built the entire blockchain-enabled backend solution
- Performed an analysis of the selected blockchain platform and technologies and initiated a POC to test the viability of the solution
- Designed a full-proof architecture including the user interfaces and admin consoles for every component of the solution
- Generated private keys via mnemonics and created a secure vault that allowed every participating bank to manage private keys
- Worked on multiple use cases to enhance productivity throughout the organization and decrease manual overheads
- Researched, designed, and implemented a machine learning approach for error avoidance during task execution
Built a platform for segmenting the customers into different clusters based on transactions in a shopping mall.
Built a tool for scheduling employees for the next week given their preferences and constraints.
Association Rule Mining:
Used association rule mining to extract association rules from a dataset representing the transactions of various customers.
Sales Yield Optimization:
Built a platform for scoring various leads based on the available information to optimize the sales pipeline.