facesearching and Virdi both work with facial biometrics, but they operate in completely different problem spaces. facesearching is an online reverse face search engine that lets anyone upload a photo and discover where that face appears across the public web. Virdi is a biometric recognition company focused on enterprise physical access control, time-and-attendance tracking, and building security. One helps you find and verify people online; the other helps organizations decide who can walk through a door. Comparing them is a useful exercise because it clarifies why a consumer who needs online identity verification should choose a web-based face search tool over an on-premise access control system. For a comparison with another enterprise-focused provider, see our facesearching vs Cognitec analysis.
Use Cases: Web Face Search vs Physical Access Control
The use-case gap is the single most important distinction. facesearching answers the question, "Where does this face appear on the public internet?" You upload a photo and receive links to social media profiles, news articles, blog posts, and videos where that face is visible. This is invaluable for online identity verification, dating safety, marketplace seller checks, and detecting impersonation. Virdi answers a different question: "Should this person be allowed through this door?" Its facial recognition terminals are mounted at building entrances, server rooms, and factory floors, comparing a live face against an enrolled employee database to grant or deny physical access. If your goal is to verify someone you met online or find a stolen photo, Virdi has nothing to offer because it does not search the web at all. For another developer-platform comparison, read our facesearching vs Kairos guide.
Feature Comparison at a Glance
The summary below highlights how the two products differ across the categories that matter most to someone choosing a face search solution.
- Primary use case: facesearching performs reverse face search across the public web; Virdi performs physical access control and time-and-attendance at building entry points.
- Deployment model: facesearching is a cloud SaaS accessed through any browser; Virdi is deployed on-premise with hardware terminals, servers, and enrollment stations.
- Database: facesearching searches billions of public web images; Virdi matches against a private, locally enrolled database of authorized personnel.
- Target market: facesearching serves consumers and businesses needing online verification; Virdi serves enterprises needing physical security infrastructure.
- Pricing: facesearching offers affordable pay-as-you-go plans; Virdi requires hardware purchases, software licenses, and installation costs.
- Output: facesearching returns clickable web links and source context; Virdi returns an access-granted or access-denied decision at a terminal.
Technology Approach
Both products use facial recognition algorithms, but the technical demands are very different. Virdi's systems must work in real time at a physical terminal, comparing a live camera feed against a small, controlled database of enrolled employees. The lighting at the entrance is relatively consistent, the subject is cooperative and facing the camera, and the database is small enough that matches are fast and reliable. facesearching's face search engine must work against the open web, where images are low-resolution, taken from odd angles, cropped, compressed, and often feature multiple faces. It indexes billions of public images and must rank the most relevant matches, then present them with context and clickable source links. These are fundamentally different engineering problems: Virdi optimizes for speed and reliability at a controlled checkpoint, while facesearching optimizes for recall and relevance across an uncontrolled, massive dataset. To learn how such systems are measured, see our facesearching vs TrueFace comparison.
Deployment Model: SaaS vs On-Premise
facesearching is a pure cloud SaaS product. There is nothing to install, no hardware to buy, and no server to maintain. You open a browser, upload a photo, and get results. This makes it instantly accessible to anyone, anywhere, with zero IT overhead. Virdi is an on-premise deployment that requires purchasing physical recognition terminals, a local server or appliance to host the biometric database, enrollment hardware and software, and professional installation. This model makes sense for a corporate headquarters that needs durable, offline-capable physical security, but it is wildly impractical for an individual who simply wants to check whether a dating profile photo is real. The deployment model alone rules out Virdi for any online identity verification use case.
Pricing and Total Cost of Ownership
facesearching's pricing is designed for individual affordability. You can run a single search for a few dollars, or subscribe to a Starter or Pro plan if you search frequently. There are no setup fees, no hardware costs, and no long-term contracts. Virdi's total cost of ownership is a different order of magnitude. A single Virdi facial recognition terminal can cost hundreds or thousands of dollars, and a full deployment across multiple entry points adds up quickly. On top of hardware, there are software licenses, maintenance contracts, and installation labor. For an enterprise securing a building, this investment may be justified. For a consumer verifying an online contact, it is both unaffordable and unnecessary. facesearching gives you the face search capability you need at a price any individual can access. Visit the facesearching homepage to see current pricing.
Target Market
- Virdi: Enterprises, government buildings, factories, data centers, and any organization that needs to control physical access to facilities using biometric identification.
- facesearching: Individuals, small businesses, freelancers, journalists, parents, and anyone who needs to verify an online identity or find where a face appears on the public web.
Privacy Features
Privacy considerations differ sharply because the data environments differ. Virdi stores enrolled biometric templates on a local server controlled by the deploying organization. The privacy of that data depends on the organization's own policies and the local biometric privacy laws it must comply with. Employees typically consent to enrollment as a condition of building access, and the data never leaves the premises. facesearching, by contrast, searches publicly available web content and does not build a persistent database from your uploads. Your uploaded photo is deleted immediately after the search completes, so there is no retained biometric template to protect or leak. For consumers, this ephemeral model is the more privacy-protective choice: you get the answer you need without leaving your biometric data behind in any system.
Virdi secures physical spaces; facesearching secures digital decisions. If your verification problem is online, you need a web-based face search engine, not a door terminal.
Why facesearching Is More Suitable for Online Identity Verification
If you need to verify someone you interact with online, facesearching is the right tool and Virdi is the wrong one. facesearching searches the open web, returning clickable links to the public sources where a face appears, which is exactly what you need to confirm or refute a claimed online identity. It is cloud-based, so you can use it instantly with no installation. It is affordable for individuals, with no hardware or contract required. And it protects your privacy by deleting your upload the moment the search finishes. Virdi's on-premise access control system is excellent for its intended purpose of physical building security, but it cannot search the web, cannot be used without hardware, and is priced for enterprise budgets. For online identity verification, the choice is clear. Ready to verify a face online? Start a free face search on facesearching now and discover where a photo appears across the public web in seconds.