Face.Match.Expert
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About
Face.Match.Expert is a cloud-based facial recognition search API designed for high-speed indexing and retrieval within massive datasets. Developed by Expertum Ltd, the platform specializes in reverse face search, allowing users to identify and match faces across millions of photos with a reported 99.98% accuracy. Unlike general image recognition tools, this system is specifically optimized for facial biometrics, converting images into unique embeddings rather than storing the original files, which ensures compliance with privacy regulations like GDPR. The technical workflow involves three main stages: account setup, data indexing, and facial matching. Developers can create unlimited collections and send batches of photos via an asynchronous API. The system extracts face embeddings—mathematical representations of facial features—and immediately deletes the original source images to maintain security. When a search is initiated, the tool compares the embedding of the query photo against the stored collection, returning a list of referral IDs sorted by similarity. The system is built for scale, having been tested on collections exceeding 500 million faces without performance degradation. This tool is primarily aimed at developers, security firms, and enterprise organizations requiring robust biometric search capabilities without the overhead of building their own AI infrastructure. It is particularly well-suited for use cases in event security, media management, and digital identity verification. The API supports standard JSON payloads and handles complex tasks like recognizing multiple faces within a single image, assigning the same user-provided ID to each distinct embedding found. What distinguishes Face.Match.Expert is its commitment to data privacy and flexible deployment. By never retaining original photos and relying solely on vector-like embeddings, it provides a secure environment for sensitive biometric data. Additionally, while the cloud-hosted version is the default for ease of use, the company offers a self-hosted storage option for enterprises and government sectors that require data to remain on-premise or within a private cloud. Its progressive pricing model also makes it accessible for startups to begin with a free tier before scaling to high-volume commercial requests.
Pros & Cons
Achieves 99.98% recognition accuracy for high-precision matching.
Searches through collections of millions of photos in just 0.1 seconds.
Complies with GDPR standards by deleting original images and only storing facial embeddings.
Scales effectively to handle collections exceeding 500 million faces without performance loss.
Provides a free tier with 1,500 requests per month and no credit card required.
Individual image uploads are strictly limited to a maximum size of 5MB.
Search functionality is currently limited to processing only one face per operation.
The API may return 401 unauthorized errors if sandbox and production credentials are mixed.
Pricing is complex, involving separate charges for add, detect, search, and delete actions.
Use Cases
Security teams at large venues like stadiums can index attendee photos to quickly identify individuals and enhance match-day safety.
Media asset managers can automate the tagging and organization of massive photo libraries by matching faces against a known database.
App developers can integrate secure biometric identity verification into their software using the GDPR-compliant cloud API.
Enterprise organizations with strict data residency requirements can use the self-hosted option to keep biometric embeddings on private servers.
Platform
Task
Features
• self-hosting options
• gdpr-compliant processing
• detailed similarity scoring
• automatic photo deletion
• multi-million face collection support
• asynchronous data indexing
• 99.98% recognition accuracy
• reverse face search api
FAQs
Are original photos stored on your servers?
No, original photos are permanently deleted immediately after the AI extracts facial embeddings. This ensures that sensitive biometric data is protected and the system remains GDPR-compliant.
What is the maximum size for uploaded images?
The system accepts image files up to a maximum size of 5MB per upload. This limit applies to all actions, including adding faces to collections and performing searches.
How does the system handle images with multiple faces?
When an image contains multiple people, the API recognizes and saves each face individually. All resulting facial embeddings are then linked to the unique ID provided by the user for that image.
How long does a typical face search take?
Searching through a collection typically takes about 0.1 to 1.5 seconds, excluding the time required for initial image processing. Performance remains stable even when searching through collections with hundreds of millions of records.
Can I host the data on my own infrastructure?
Yes, Face.Match.Expert offers a self-hosted deployment option for enterprises and government sectors. This allows face embeddings to be stored on your own on-premise servers or within a private cloud.
Pricing Plans
Cloud-hosted (Standard)
EUR0.94 / per 1,000 requests• Progressive pricing tiers
• Unlimited collection storage
• Storage billed at €0.01 per 1,000 records
• Stable and secure cloud environment
• Automatic monthly settlement
• Supports 100M+ total requests
Self-hosted
Unknown Price• On-premise deployment
• Private cloud storage
• Ideal for government sectors
• Full control over biometric data
• Custom solution pricing
• Enterprise-grade technical support
Free
Free Plan• 1,500 API requests per month
• 1,000 photos in collection storage
• No payment details required
• Asynchronous API processing
• GDPR-compliant data handling
• Access to facial embedding extraction
Job Opportunities
There are currently no job postings for this AI tool.
Ratings & Reviews
No ratings available yet. Be the first to rate this tool!
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