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Digital businesses are increasingly facing a problem that is difficult to detect with traditional analytics: not every visitor is a unique, legitimate user.
One person can have multiple accounts, repeatedly take advantage of promotional offers, share a paid account, or use a VPN, proxy, or anti-detect browser to access a service. That activity can distort traffic data and create financial and security risks for SaaS companies, marketplaces, fintech platforms, and other online businesses.
Founded in 2025, SaaS company ShieldLabs is building fraud detection and prevention technology with traffic quality scoring. The platform is designed to detect users running multiple accounts, account sharing, and account takeovers under any masking, helping companies prevent losses from free-trial, bonus, promotional, and API abuse.
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What ShieldLabs Can Do
ShieldLabs describes itself as fraud detection and prevention with traffic quality scoring. Its technology is designed to help businesses understand traffic quality while detecting different forms of fraudulent and abusive activity.
The platform analyzes signals across devices, browsers, operating systems, IP addresses, and networks. ShieldLabs says it directly detects multi-accounting, account sharing, account takeover, and impossible travel out of the box, with each detection assigned a Medium or High confidence level.
These capabilities can be particularly relevant for businesses where abuse can quickly translate into financial losses. SaaS companies, for example, may need to identify users repeatedly creating accounts to exploit free trials, while platforms offering promotions or bonuses may need to distinguish legitimate users from coordinated abuse.
The Significance of Anonymous Traffic
For many online businesses, fraud prevention happens after suspicious activity has already taken place. ShieldLabs takes an earlier approach by examining visitors, devices, accounts, and surrounding signals before an organization has to decide how to respond.
Consider a SaaS company offering a free trial. One person could potentially create multiple accounts and repeatedly use the offer. A marketplace could encounter users operating multiple accounts, while a business running paid advertising could find that some of its traffic is coming through anonymizing services.
ShieldLabs focuses on use cases including multi-accounting, account sharing, account takeover, promotional abuse, traffic-quality analysis, and related forms of online abuse. By connecting visitors, devices, and accounts, the platform aims to make relationships between seemingly separate activities easier for businesses to identify.
For companies where user acquisition and conversion metrics directly affect business decisions, identifying suspicious traffic can also provide an analytics benefit. Traffic-quality information can help businesses understand where visitors are coming from and distinguish potentially abusive activity from legitimate traffic.
A Clear Alternative to Black-Box Risk Scores
One of the notable aspects of ShieldLabs’ product is its focus on explainability.
Instead of presenting only a risk score, the platform shows the named signals that contributed to it. These can include VPN, proxy, Tor, Apple Private Relay, datacenter IP, anti-detect browser, and browser automation.
ShieldLabs says its platform also detects bots and AI agents and separates bad bots from good ones.
The product generates a Risk Score from 0 to 100 for every visitor, user, device, and IP address, alongside the named signals associated with that assessment. This gives teams more context when deciding how to handle potentially suspicious activity.
According to ShieldLabs, the platform has 99.9% identification accuracy and 99.9% risk signal detection accuracy.
Built for Smaller Teams
ShieldLabs is also positioning itself as an alternative to the cost and complexity traditionally associated with enterprise fraud and visitor-intelligence products.
The company offers self-serve access and transparent pricing. Its free plan includes 5,000 identifications.
The paid plans include Starter at $99 per month for 25,000 identifications, Growth at $399 per month for 150,000 identifications, and Scale at $999 per month for 500,000 identifications. ShieldLabs also offers discounts of up to 20% on annual billing.
Implementation can start with a JavaScript snippet, after which teams can connect the platform to their systems through APIs and webhooks. ShieldLabs’ documentation provides integration options for different visitor and user scenarios.
Where It Might Be Useful
ShieldLabs serves multiple industries.
The company identifies SaaS, fintech, e-commerce, marketplaces, travel, media and streaming, ticketing, gaming, and other online businesses as potential use cases.
The underlying idea is similar across these markets: determine whether seemingly different accounts, sessions, or visitors may actually be connected and identify signals that indicate elevated risk.
Its technology can help businesses identify activity associated with multi-accounting, account sharing, account takeover, promotional abuse, and other forms of suspicious behavior.
For security teams dealing with credential stuffing, visitor and device-level signals can also provide another layer of context alongside existing authentication and fraud-prevention systems. Organizations such as OWASP have well documented the broader cybersecurity challenge.
The company also highlights Web3 as another potential application, where identifying connections between visitors and accounts can help detect potential Sybil activity.
Detection That Helps Block Fraud
ShieldLabs’ approach is to provide the detection and risk intelligence that businesses can use within their own systems.
The platform identifies users and sessions, analyzes relevant signals, and provides a Risk Score alongside the signals behind it. From there, businesses can allow the visitor through, add a verification step or block the action.
That could mean allowing a visitor to continue normally, challenging the visitor with additional verification, or blocking the activity altogether.
This approach gives development and security teams flexibility. ShieldLabs can act as an intelligence layer that feeds information into an existing authentication, fraud, or moderation system rather than replacing it.
This can be particularly useful for businesses that want to introduce additional risk signals without completely redesigning their existing user-management infrastructure.
The Road Ahead
ShieldLabs is still a young company, founded in 2025. Its product is built around challenges such as anonymized traffic, anti-detect browsers, multi-accounting, account sharing, account takeover, bots, AI agents, and other forms of online abuse.
The longer-term question will be how effectively its detection signals perform across different environments and how businesses translate those signals into practical decisions.
For now, ShieldLabs is taking a focused approach: identify who is visiting, expose the signals behind their activity, and give businesses more context before they decide what to do.
As online businesses face increasingly sophisticated forms of abuse, better visibility into who — or what — is actually behind a visit could become an increasingly important part of maintaining trustworthy traffic, accurate analytics, and sustainable customer acquisition.
