SightRadar
find a person across thousands of photos from one selfie1:1 verification with scores you set the threshold onsame request & response shapes as AWS Rekognitionpoint your existing SDK at one new endpointa photo with 0 faces is a valid result, not an errorpay only for what you use · billed per photo, never per facefind a person across thousands of photos from one selfie1:1 verification with scores you set the threshold onsame request & response shapes as AWS Rekognitionpoint your existing SDK at one new endpointa photo with 0 faces is a valid result, not an errorpay only for what you use · billed per photo, never per face

face recognition API

High-accuracy face recognition APIs.

Index, search, compare, and detect faces at scale — with confidence scores you can threshold on.

Already using AWS Rekognition? Our APIs are compatible — point your existing SDK at one new endpoint and ship.

Start free — no card Try the live demo

Pay only for what you use · billed per photo, never per face · no minimums.

Why teams switch
CHEAPER ALL ROUND

Cheaper than AWS, Azure and Face++

from $0.00062 a photo — half the AWS Rekognition rate. run the numbers yourself

PROVEN AT SCALE

Millions of photos, in production today

the same engine runs live event galleries — proven on real traffic, not a demo

GDPR READY

A real DPA, and deletion that actually works

Article 28 processor terms, Article 15/17 subject requests, never trained on your data

Run your own selfie against the live demo below.

don't take our word for it

See it recognize faces — with the JSON.

Search a gallery from one selfie, verify two faces 1:1, or detect and quality-gate. Every tab shows the actual Rekognition-shaped response, so you can see the engine is real and the API is compatible.

Query selfie

Query selfie

4 matches · 41ms

Collection (8 photos)

match0.95
no match0.41
match0.96
no match0.38
no match0.44
match0.92
no match0.36
match0.97
API responseRekognition-compatible
// SearchFacesByImage response
{
  "SearchedFaceConfidence": 99.81,
  "FaceMatches": [
    { "Similarity": 98.1, "Face": { "FaceId": "b3f1…a7" } },
    { "Similarity": 97.4, "Face": { "FaceId": "c2a4…b9" } },
    { "Similarity": 96.7, "Face": { "FaceId": "7e51…62" } },
    { "Similarity": 97.2, "Face": { "FaceId": "9a04…e2" } }
  ]
}

Faces shown are AI-generated — these people don't exist. The matched shots are the same generated identity with real appearance changes (glasses, clean-shaven, aging, different lighting and settings). Scores are representative; published benchmarks on public datasets are coming.

why teams pick SightRadar

Two reasons it sticks.

Accuracy you can ship on

Tuned embeddings hold up across pose, lighting, and age. High-confidence matches, calibrated scores you can threshold — not a toy demo.

Rekognition-compatible API

Same request and response shapes as AWS Rekognition. Point your existing SDK at our endpoint and your IndexFaces / SearchFacesByImage / CompareFaces calls just work.

migrate without a rewrite

Keep your code. Swap the endpoint.

SightRadar speaks the same request and response shapes as AWS Rekognition. Use the AWS SDK you already have — set one endpoint_url and your existing calls keep working.

Supported operations

  • CreateCollection
  • IndexFaces
  • SearchFacesByImage
  • SearchFaces
  • CompareFaces
  • DetectFaces
  • ListFaces / DeleteFaces
  • ListCollections / DeleteCollection
import boto3

rek = boto3.client(
    "rekognition",
    # the only line you change:
    endpoint_url="https://api.sightradar.com",
)

# your existing calls, unchanged:
rek.search_faces_by_image(
    CollectionId="guests",
    Image={"Bytes": selfie},
    FaceMatchThreshold=80,
)

four moves, one clean API

Everything you need to see faces.

Index

Detect every face in a photo and store its embedding in your collection.

Search

Find every photo a person appears in from a single selfie.

Compare

Similarity between two faces — verify identity 1:1.

Detect

Locate and quality-gate faces without storing anything.

honestly, it's three steps

Set it once. Then just call it.

1

Grab a key

Open the console, add credits, copy your API key.

2

Index your faces

POST photos to a collection. We detect, embed, and store every face.

3

Search & verify

Send a selfie or compare two faces. Same calls you already know.

handle faces responsibly

Sensitive data, treated that way.

Face data is biometric and sensitive. We keep our practices deliberately narrow — and write them down in plain language.

You control retention

Detect and compare process images in memory and don't persist them. Indexed faces live in collections you can delete any time, via API or console.

Isolated & encrypted

Each account's face vectors are namespaced and never cross-searchable. Encrypted in transit, scoped API keys, per-tenant isolation.

Never trained on your data

We process your data only to return your results. We do not pool it or use it to train general-purpose models, and we never sell it.

Built for consented use

You're the data controller. Our Terms require a lawful basis and consent — and prohibit unlawful surveillance or covert tracking.

Read the full Privacy Policy and Terms.

and yes — it costs less

The same accuracy, a smaller bill.

You switch for the accuracy and the drop-in migration — the lower bill is just the part finance likes. Pay only for what you use, billed per photo processed (never per face) — no surprise bills. Control-plane calls are free.

  • Real-time — $0.00093 per photo processed
  • Batch — $0.00062 per photo processed
  • Search by face-id — $0.00062 · storage $6 / M / mo
See full pricing & calculator

Batch indexing

$0.00062

per photo processed

Pay only for what you use — no subscription, no minimums, no surprise bills. See the calculator for a side-by-side with AWS Rekognition.

Start with pay-as-you-go

Ship face search this week.

Free to start, pay only for what you use. Your first match in minutes — no rewrite.

Get your API key — free