Avagance is still in its beta stage, yet the ambition behind it is already shaping a clear path. Built under Bro in Finance Ltd by co-founders Lithika Ranepura and Dinuwan Fernando, the platform aims to become an AI trading super app that brings together forecasting, natural language strategy building, execution, analysis, tax tools, and curated financial content in one place. The idea is simple to describe but hard to build.
Most investors bounce between several apps just to manage basic tasks. Avagance is being designed to close that gap.
The story began far from the fintech hubs of London. Lithika first entered entrepreneurship through Britanna Medicare, a cosmetic medical clinic he founded in Kandy, Sri Lanka. He grew the business to a team of full-time staff and medical specialists and eventually exited at twice the audited annual net profit. That experience taught him the value of reliable operations, clean financials, strong brand positioning, and solid governance. These are lessons he later applied directly to building a technology company.
During his MSc in Investment at the University of Birmingham, he developed a hybrid 3ANN–LSTM forecasting model for crude oil prices and earned a Distinction for his thesis. That academic project planted the early idea for a multi-asset prediction engine. Once he moved into fintech full-time, the concept expanded into a deeper vision. Short-term forecasts became only one layer of a much wider system.
Inside Avagance, artificial intelligence is at the centre. Machine learning models run weekly predictions across forex, equities, crypto, and commodities. Users can describe trading ideas in natural language and convert them into automated strategies that can be tested and deployed. Smart Portfolios allow fully managed accounts based on individual risk levels. A tax engine can read trades across accounts and produce capital gains reports suitable for local regulators, beginning with the UK and expanding later to other regions. The platform also includes a curated social feed where qualified analysts and writers can publish insights and earn revenue.
Lithika and Dinuwan spent more than a year building the system almost nonstop, refining infrastructure, testing new models, and rebuilding interfaces as more advanced techniques became available. Their work ethic and willingness to re-engineer features led the platform to evolve beyond its original academic roots. It is now shaping into an application designed for both retail and institutional users, with a technology layer that multiple brokers can eventually integrate with.
Avagance remains in beta, and the team is preparing for a seed funding round. Their goal is to accelerate development, expand deep learning capabilities, and scale the marketplace for user-generated strategies. The long-term ambition is a global platform where investors can research, trade, analyse, automate, and manage tax obligations inside one streamlined ecosystem.
