SightRadar

SightRadar is a face recognition API for teams that need face search, verification and detection at scale, without AWS Rekognition's pricing. It is Rekognition-compatible: point the AWS SDK (boto3 and others) at SightRadar's endpoint and your existing code keeps working. What you get: - Face search: find one person across thousands of photos from a single selfie (event photos, media libraries, photo delivery) - 1:1 verification: compare two faces with a similarity threshold you choose - Face detection with confidence scores you can threshold on - Rekognition-compatible API: CreateCollection, IndexFaces, SearchFacesByImage, CompareFaces, DetectFaces and more - Photos with no faces return valid empty results, not errors - Per-photo billing, never per face: batch indexing from $0.00062 per photo, real-time $0.00093 per photo - Privacy by design: GDPR-ready with a Data Processing Agreement, face vectors isolated and encrypted per account, never used for model training - SDKs on npm and PyPI, plus a Rekognition shim for Python Free to start with trial credits, no credit card required. Pay-as-you-go prepaid credits, no subscription and no minimums.

SightRadar offers high-accuracy face recognition APIs that enable users to index, search, compare, and detect faces at scale. The service provides confidence scores that users can adjust, catering to various verification needs. It is designed for teams seeking a reliable and cost-effective alternative to existing solutions like AWS Rekognition, ensuring that they only pay for the photos processed without hidden fees. Users interact with SightRadar by indexing faces from images which are then stored for future searches and comparisons. They can send selfies or image files to the API and receive JSON responses that indicate similarity scores and face matching information. The API supports the same request and response shapes as AWS Rekognition, allowing seamless integration for existing users of that platform. SightRadar is intended for developers and teams looking for an efficient face recognition solution that is easy to integrate and provides cost-effective billing. It caters to various industries that require biometric verification, especially those already using AWS Rekognition, by allowing them to migrate without extensive changes to their existing codebases.