OSINT Industries: A Spotlight on Real-Time Investigations

OSINT Industries lets an investigator type in an email address, phone number, or username and see the public accounts tied to it, pulled from more than 1,500 sources (OSINT Industries). The company says it supports over 5,000 law enforcement departments worldwide. It's also a Massive customer, and its product design makes the web-reach question unusually concrete.

Key Takeaways

• OSINT Industries searches 1,500+ public sources and supports 5,000+ law enforcement departments, per its own site.
• It gathers data in real time and says it never stores searches or results, so each lookup has to reach live pages.
• In 2025 the FBI logged over 1 million cybercrime complaints and nearly $21 billion in losses (IC3 2025 report).
• Real-time lookups depend on requests reaching public pages the way an ordinary visitor would.

What does OSINT Industries do?

OSINT Industries is an open-source intelligence platform that turns one identifier into a picture of the public accounts linked to it. An investigator enters an email, phone number, username, name, or crypto wallet, and sees the results in one view, with mapping and timeline tools and exports to PDF, DOC, Excel, or JSON (OSINT Industries).

That matters because the caseload keeps growing. In 2025, the FBI's Internet Crime Complaint Center logged more than 1 million complaints for the first time, with reported losses of nearly $21 billion, up 26% on 2024 (FBI IC3, 2025 Internet Crime Report). Many of those cases start with one question: who is actually on the other end?

The customer list reads like a map of who fights fraud for a living. OSINT Industries names law enforcement, government agencies, journalists, private investigators, insurance and fraud teams, cybersecurity professionals, legal teams, and non-profits (OSINT Industries). It also serves anti-money-laundering (AML) teams (OSINT Industries AML), and it offers free access to government, law enforcement, journalism, and non-profit organizations (OSINT Industries API).

Why does a real-time, no-storage model matter?

OSINT Industries says its API data is "gathered in real time" and that searches and results are "never stored" (OSINT Industries API). That's a deliberate choice. It changes what the product has to do on each search.

A stored database answers from a snapshot. It's quick. But it goes stale as soon as an account is renamed, deleted, or created, and nobody notices until a result turns out to be wrong. A real-time model checks the live sources when the investigator asks, so the answer reflects the web as it is right now, not as it was when someone last took a snapshot.

The no-retention half matters just as much. OSINT work touches personal data, and investigators need to justify how they handle it. A tool that keeps no copy of searches or results has less sensitive data sitting around to leak, subpoena, or misuse. For a fraud team or a newsroom, that's easier to defend.

Why are live lookups hard at scale?

Sites now treat automated traffic with suspicion, so a legitimate lookup tool gets blocked, geo-shifted, or slowed the same way a spam bot does. The reason is volume: in 2025, bots made up 53% of all web traffic, according to Imperva's 2026 Bad Bot Report (Imperva).

That creates three practical problems for any live-lookup product:

• Blocking and rate limits. Many requests from one datacenter address look like a bot. So they tend to get throttled, challenged, or refused.
• Location-dependent answers. Some platforms show different pages, or different sign-up and recovery flows, depending on the visitor's country.
• Speed. An investigator is waiting on the result. A lookup that fans out across hundreds of sources can only move as fast as its slowest reachable page.

None of this is about parsing or analysis. It's about whether a request reaches the real public page at all. And a lookup that quietly fails on one source doesn't throw an error. It just returns a thinner result, and the investigator may never know what's missing.

Picture a fraud case. An analyst checks whether a phone number used in a scam links to other accounts. If three sources quietly refuse the request, the result looks clean when it isn't. For a real-time product, reach is part of accuracy.

Where Massive fits

Massive runs a network of over 1 million real, opted-in consumer devices in 195+ countries (Massive docs), about 1.3 million daily active devices by our internal count. Requests routed through it arrive the way ordinary local visitors do. Massive provides the network. OSINT Industries builds and runs its own product and its own investigations workflow, and Massive doesn't touch that side.

Every device on the network opted in through the Massive SDK. The network is covered by SOC 2 audit, GDPR compliance, and AppEsteem certification, with an audit trail from source to request. You can read how that consent model works in our transparency report on the opt-in network.

Why does sourcing matter more for OSINT than for most use cases? Investigators often have to explain their methods to a court, an editor, or a compliance officer. The tools under their workflow need a provenance story that holds up, and consent-based sourcing is part of that story. The wider case for it is in our piece on ethically sourced web access.

What can other investigation and trust-and-safety teams learn from this?

Build for live data if your answers need to reflect today, and treat reach as a measure of accuracy. The stakes keep rising: the FTC says people reported losing about $16 billion to fraud in 2025, "the highest on record" (FTC, June 2026). OSINT Industries' design choices make a useful checklist for teams building their own lookup and verification tooling.

1. Decide whether you need live data or a snapshot. Account-linkage work goes stale quickly. If your answers need to reflect today, plan for live requests.
2. Treat reach as a quality metric. Track how often each source actually returns a usable page, not just whether the job finished.
3. Match the visitor's location to the question. If a platform behaves differently by country, fetch it from that country.
4. Keep only what you need. Retaining less personal data is usually easier to defend than retaining more.
5. Know where your traffic comes from. If your methods get scrutinized, the sourcing of your network is part of your answer.

If you're weighing network size while you do this, count devices, not IPs. Our myth-busting piece on IP counts explains why.

The takeaway

OSINT Industries made two choices that many data products avoid: look everything up live, and keep nothing afterward. Both make its results more useful to the 5,000+ law enforcement departments and the fraud, legal, and newsroom teams it serves. Both also mean each search depends on reaching real public pages, from the right place, at the moment someone asks. That's the kind of problem Massive's network is built for, and we're glad to work alongside a team whose product is built for the investigators who close these cases.

About the author: Franklin Uche covers web data infrastructure, proxy networks, and AI-agent access for the Massive blog. Read more on Massive's About page, or reach the team directly by booking a call.

Sources

• FBI Internet Crime Complaint Center, 2025 IC3 Annual Report
• Federal Trade Commission, "FTC Data Show People Reported Losing $3.5 Billion to Imposter Scams in 2025", June 15, 2026 (states total 2025 fraud losses of "about $16 billion," "the highest on record")
• Imperva, 2026 Bad Bot Report: Bots in the Agentic Age
• OSINT Industries, home page
• OSINT Industries, API Access
• OSINT Industries, Anti-Money Laundering
• Massive, Residential Proxies introduction