Today, an increasingly important part of investigations involves data analysis, the reconstruction of connections, and the ability to read what, at first glance, does not appear to be directly interconnected.
A recent case that clearly demonstrates this is the investigation conducted by Bubblemaps into Polymarket.
For those unfamiliar with it, Polymarket is a prediction market platform, meaning a market where users can bet on the outcome of future events: elections, political decisions, geopolitical scenarios, economic or military events.
In this context, certain accounts had placed particularly profitable bets on sensitive geopolitical events, placing wagers shortly before certain scenarios materialized.
At first glance, it could have seemed like a simple story of very lucky traders.
-Different accounts;
-Different wallets;
-Unrecognizable names;
-Apparently autonomous transactions.
But Bubblemaps, a company specialized in blockchain data analysis, analyzed the matter from another perspective.
It did not merely observe who had earned the most or which bets had proved successful. It analyzed the connections between wallets, money movements, intermediate transfers, and the links between different addresses.
In other words, it sought to understand whether those accounts were truly independent or whether, behind apparently separate profiles, there might be a coordinated network.
What Bubblemaps did
Bubblemaps’ work is interesting because it shows, in a very concrete way, how a digital investigation can work.
Each wallet, taken individually, could appear as an autonomous entity. But by observing the movements as a whole, connections emerged: transfers between addresses, common funding, similar timings, transactions concentrated on the same events.
The focus therefore shifted from trying to understand who had placed a specific bet to understanding whether one or more accounts were moving together.
In the digital world, in fact, what appears separate is not always truly so. Multiple accounts, wallets, or profiles may seem independent, but if they share flows, behaviors, timings, and connections, they can tell a different story or reveal a possible pattern.
This does not automatically mean that there was unlawful conduct or the use of privileged information. That is an assessment that may fall to the competent authorities and requires further verification. But from an investigative standpoint, the signal is clear: when multiple apparently autonomous elements present coherent, recurring, and temporally synchronized behaviors, it is worth investigating further.
After all, isolated accounts and wallets may reveal little, just like a single apparently random transaction; but when multiple elements begin to repeat, overlap, or move in the same way, the picture changes.
It is the same logic that can be applied in many investigative activities: reputational analyses, counterparty checks, anti-fraud investigations, corporate reconstructions, coordinated online activities, or the identification of opaque networks.
It is not only about collecting information; it is about understanding whether that information, when put together, may indicate organized behavior.
What it means from an investigative perspective
The lesson of the Bubblemaps–Polymarket case is that, in the digital world, traces are not always evident, but often exist in the form of weak signals: a transfer, recurring timing, an intermediate connection, a repeated behavior.
Taken individually, these elements may seem of little relevance. Observed as a whole, however, they can reveal a network and change the overall interpretation of the case.
For this reason, investigative activity cannot limit itself to asking who is behind an account, but must also understand which subjects interact with one another, where the funds come from, which connections recur, and whether multiple apparently separate elements are moving in the same direction.
The case demonstrates precisely this: what appeared to be a series of individual bets, through connection analysis, took on a possible different interpretation. Not definitive proof, but certainly a relevant investigative indication.
The real lesson is that different accounts do not always mean different subjects, separate wallets do not always mean separate interests, and isolated transactions are not necessarily random behaviors.
For this reason, today, a fundamental part of intelligence consists in reconstructing hidden connections, reading weak signals, and transforming fragmented data into a coherent representation.
The Bubblemaps–Polymarket case represents a significant example of the evolution of the investigative sector: the digitalization of economic, financial, and reputational relationships requires investigative agencies to constantly update methods, tools, and skills. It is no longer sufficient to operate according to exclusively traditional logics. Investigative firms must be able to integrate field activity, OSINT analysis, data interpretation, and the reconstruction of digital connections.
It is also in this area that Vigilar Group continues to invest in order to offer solutions increasingly aligned with the complexity of the contemporary context.
English 
Italian