Thirty Thousands Lenses

DRAGONFLY'S PROPRIETARY AI DATA DASHBOARD

A dragonfly sees in almost every direction at once, waits with perfect stillness, and moves only when something real happens. We are building our research capability in the same shape.

Institutions have arrived in Crypto. The tools to analyse it have not. So we built our own.

A market at its revenue stage, with no way to read the accounts.

Crypto has crossed the line from speculation into cash generation. Protocols now earn real fees from real users, and those fees can be measured, compared and valued. What the sector still lacks is the machinery traditional finance takes for granted: standardised reporting, comparable metrics, and a single screen that lets a professional investor put the same question across the market at once.

This is not our complaint alone.

When Nomura asked 518 investment professionals what stands between them and digital assets, one of the leading answers was the absence of an established framework for fundamental analysis. Meanwhile nearly three quarters of the institutions surveyed by Coinbase and EY-Parthenon plan to increase their allocations in 2026. Capital is arriving into a market with no instrument panel.

Built for traders, not for fund managers.

Understanding a Crypto protocol today is less like analysis and more like archaeology: digging through half a dozen data sites, each with an awkward interface and data of uncertain veracity. The existing Crypto platforms were mainly built for Crypto’s original users: day traders and retail investors. None was designed around the workflow of a TradFi asset manager screening a universe for ideas and monitoring the positions already held. So the professional investor assembles disparate sources by hand, every morning, and hopes nothing is missing. The arithmetic does not work, in time or in people.

So we changed the arithmetic.

Dragonfly’s AI dashboard analyses a digital asset the way a fund manager analyses a company. It ignores the price and hunts for meaningful change in the business behind it: a step change in users, an inflection in revenue, a material shift in what the token returns to the people who hold it. It aggregates onchain data and financial metrics across the top liquid tokens, and it tells us where to look. Standardising that data and separating signal from noise remains an engineering problem and an active area of research for us. The dashboard is live. It is also early, and it improves every month.

The edge is not the software.

Anyone can aggregate data. We built the dashboard because we already knew what to look for. The hard judgement is knowing which metrics matter and which are decoration, and that judgement is the product of decades spent valuing technology businesses. AI does not replace the fund manager. It makes the fund manager better. It removes the slow work of digging for data, and hands a better and timelier shortlist to the part of the process no software touches: our six pillars of analysis, our conviction tiers, and the decision to act.

Coverage that does not grow with headcount.

Our ambition is a system of AI agents, each reading a corner of the market around the clock, each trained to recognise a fundamental shift and trace what it means for every position we hold. Our costs stop growing with our universe, and our universe stops being limited by our costs. That is the whole argument for building this in-house, and it is why we regard the dashboard as the most durable piece of infrastructure the firm owns, after the judgement of the people who use it.

Bloomberg and Reuters were built for professional investors, not for Crypto. The data platforms built for Crypto were not built for professional investors. Somebody will close that gap. Nobody has closed it yet, so we stopped waiting and built our own.

A dragonfly sees in every direction. It waits. And when something real changes, it moves.