Co-Founder & CEO
A driving force behind JungleTrade, Ivaylo combines extensive technical experience with a strong entrepreneurial background. As a serial entrepreneur, he has built and developed businesses from the ground up and today focuses on turning ideas into scalable products and sustainable companies.
Co-Founder & CEO
Dragomir combines experience in financial markets, data analysis, software development, and engineering. At JungleTrade, he focuses on product strategy, quantitative market intelligence, and the development of data-driven tools that transform complex market information into practical insights for traders, analysts, and financial professionals.
Product Strategy Advisor
Vlad brings experience in product strategy, investment, and business development. At JungleTrade, he advises on product direction, market positioning, and the practical needs of investors and financial professionals, helping align the platform’s development with real-world market use cases.
Full Stack Developer
Valentin contributes to JungleTrade’s platform development and technical architecture. With experience in full-stack development, microservices, and system implementation, he helps ensure the platform remains robust, scalable, and reliable as it continues to evolve.
JungleTrade powers J.Labs' ecosystem of quantitative trading, monitoring, and AI-assisted market analytics systems.
Designed for modern financial applications, the platform integrates structured market data, analytics, indicators, quantitative models, and market triggers within a unified architecture built by traders and developers who have experienced firsthand the challenges of fragmented APIs, unreliable data, and missed trading opportunities.
Unified realtime and historical datasets across financial and digital asset markets.
Indicators, statistical models, and market condition analysis designed for quantitative workflows.
Signal generation and analytical systems built for monitoring, automation, and decision support.
Low-latency architecture designed for modern financial applications and trading systems.
Integrated AI and machine learning systems for advanced market interpretation and analytics.
Modern financial systems are built on data, yet too much of that infrastructure remains fragmented, inconsistent, and difficult to integrate.
JungleTrade was created to unify this infrastructure within a single architecture designed for modern financial applications.
Built by professionals who understand the operational challenges of real-world market environments firsthand, the platform is designed to power the development of trading, monitoring, analytical, and decision-support systems through structured and scalable market infrastructure.
Our goal is to build the infrastructure behind the next generation of financial applications — from automated trading systems and portfolio intelligence platforms to quantitative research and risk management solutions.
From a Quantitative Research Lab to a Full Market Ecosystem
Modern financial and decision-making systems no longer rely on a single market indicator or isolated dataset. Building trading, monitoring, and analytical platforms today requires combining vast amounts of information — from macroeconomic data and market sentiment to realtime trading activity and cross-market influence.
As financial infrastructure becomes more complex, integrating and maintaining multiple APIs, data streams, collection services, and analytical systems becomes increasingly difficult, expensive, and operationally demanding.
Endpoint changes, inconsistent responses, realtime processing requirements, data integrity, monitoring reliability, and infrastructure scalability are just some of the technical challenges modern financial applications must continuously solve.
We believed there had to be a better way to build modern financial applications.
What if market data, analytics, indicators, quantitative models, and monitoring infrastructure could exist within a single ecosystem — a unified source of truth designed specifically for modern trading and analytical systems?
What if developers and analysts could build realtime trading applications, monitoring platforms, portfolio systems, or research environments without spending months managing fragmented APIs, disconnected services, and constantly changing integrations?
What if access to financial infrastructure was modular, scalable, and focused only on the information truly needed — without unnecessary complexity, rigid package structures, or expensive enterprise integrations?
These questions became the foundation behind JungleTrade.
Built from real operational experience, JungleTrade was designed as a unified market analytics infrastructure that simplifies the development of trading, monitoring, research, and decision-support systems through structured data, analytics, quantitative models and infrastructure delivered within a single architecture.
We put our products where our conviction, experience, and passion truly are — JungleBot. J.Labs' automated trading platform is currently being rebuilt from the ground up on top of JungleTrade, because we will not ship trading automation on anything less than the best data infrastructure we know how to build.
JungleBot is not just a product built on JungleTrade — it is proof of the infrastructure standards we expect from every system we create.
We build the infrastructure we wish existed when we started developing quantitative and automated trading systems ourselves.
The principles that guide everything we do
Reliable financial systems begin with reliable data. We source information from trusted providers and continuously validate datasets to maintain consistency, accuracy, and operational reliability across our infrastructure.
Modern financial infrastructure should be powerful without being unnecessarily complex. We focus on clean APIs, structured responses, scalable architecture, and developer-first integration workflows designed to simplify implementation.
Low latency, realtime processing, and infrastructure reliability are not optional features — they are foundational requirements for modern trading, monitoring, and analytical systems.
Financial markets are interconnected. From equities and forex to crypto, commodities, and macroeconomic data, we build infrastructure designed to support globally connected financial applications.
Modern financial applications require more than raw market data. We design systems capable of integrating multiple tools and AI-assisted analysis within a unified architecture.
We believe modern financial infrastructure should be modular, transparent, and accessible. No restrictive package bundles, unnecessary complexity, or oversized subscriptions — only the services and information truly needed to build scalable financial systems.
JungleTrade powers a growing ecosystem of financial applications built around automation, analytics, portfolio intelligence, and market infrastructure. It serves as the data and analytics backbone of a broader suite of trading, monitoring, and quantitative systems developed by J.Labs.
A secure, AI-assisted trading platform designed to automate execution layers, trading workflows, and market strategies across centralized exchanges.
Built on top of JungleTrade's unified market infrastructure, JungleBot combines realtime market data, analytics, signals, and automation within a highly flexible layered architecture. The platform simplifies automated trading for retail users while providing scalable white-label solutions for enterprise brands and trading platforms.
A professional-grade portfolio intelligence platform designed to bring institutional-style risk analysis, portfolio optimization, and quantitative portfolio management to digital asset investors.
Powered by JungleTrade's analytics infrastructure, Coconut helps bridge the gap between speculative trading and risk-adjusted portfolio management through automated balancing, quantitative analytics, and realtime market monitoring.
Join the developers and trading teams who already use JungleTrade as their data backbone. Get your API key and start building today.