Cloud Biometric MFA™ & Cloud Biometric Search™ quickly, securely and privately identify and authenticate millions of employees, partners and customers across all browsers, platforms and devices using face, voice and fingerprint recognition.
Identity is the keystone of security and commerce. Identify, authenticate, search and protect your workforce, partners and customers across all browsers, platforms, devices and geographies in polynomial time using a broad range of data and passwordless MFA options including face, voice and fingerprint recognition, passive & active liveness, WebAuthn and FIDO2 authenticators.
Private Identity® never stores, transmits or uses biometric templates. Instead, we use a mobile DNN to create a small 1-way hash of the biometric at the Edge. The original biometric is immediately discarded and all subsequent match and search operations occur in the encrypted space using Homomorphic Encryption (HME).
In addition to absolute privacy, our recognition algorithm also achieves absolute accuracy (IR=99.99%), no false positives (FPIR=0.0001% in open and closed sets), highly scalable performance (200ms), and full compliance with CCPA, BIPA, GDPR and data privacy laws worldwide.
Get started easily with SaaS and PaaS integrations, no upfront costs, no hardware to buy and no client software to install.
Private Identity® provides biometric identity, authentication, verification and search without the need to store or process usernames, passwords, email addresses, tokens, shared secrets or any other Personal Identifiable Information (PI).
Private Identity® protects individual privacy and complies with worldwide data privacy laws by never storing, transmitting or using (at rest, in transit or in use) a biometric as specified in IEEE 2410-2019.
To accomplish this, we use two DNNs that work hand-in-hand to encrypt and classify each biometric. The first DNN is a pre-trained mobile CNN that leverage TensorFlow at the Edge to acquire, pre-process, 1-way hash and then discard face, voice and fingerprint biometrics.
The second DNN is a pre-trained FCNN that classifies each 1-way hash and is capable of processing an unlimited number of identities in constant time using fault-tolerant, elastic Kubernetes™ container(s).
The first and second DNNs are pre-trained in order to allow for rapid processing at the Edge and in the Cloud. For operations without a client, both DNNs deploy to Node.js or any public or private Cloud.
Start small and scale up to billions of employees, customers and partners without human intervention, even during peak usage.
Our microservices architecture is composed of three lightweight, elastic Kubernetes™ building blocks (enroll, predict and liveness) that communicate using RESTful APIs. These services provide resilience and scalability, enable customers to go to market faster and easily integrate and deploy with legacy and third-party services.
Private Identity® encrypts biometrics at the Edge using an ensemble of ML inferences of pre-trained TensorFlow™ mobile models to assure full data privacy and confidentiality. Edge computing removes the requirement to store, transmit or use plaintext biometrics, reduces data flow to the cloud by 99.95%, achieves massive horizontal scalability and enables users to authenticate offline.
We help lead development of Open Standards for biometric privacy, cryptography and security to help foster innovation and competition. And, we partner with leading organizations to perform full-scope assessments, penetration tests, reviews, audits and IEEE and ISO certifications.
Authenticate any browser, device or platform into AAD, AWS or GCP in 200ms using passwordless face, voice and fingerprint recognition. Supports AAD, SAML 2.0, OAuth 2.0/OIDC and WebAuthn. Fully compliant with BIPA, CCPA and GDPR.
Search for face, voice and fingerprint in any video, audio or image data in polynomial time. DNN accommodates unlimited classes, blurry images, poor lighting and background noise. Minimum face and fingerprint image is 244x244. Minimum voice probe is one second of any spoken voice at 8.1kHz (telephone quality). Fully compliant with BIPA, CCPA and GDPR.
Identity proofing, KYC and workforce onboarding using passport, driver’s license and other official documents. Enroll users, compare photo on ID card to the enrollment, compare name and address on ID to user’s mobile phone records. Supports active and passive liveness. All processing completed on the local device to fully comply with BIPA, CCPA and GDPR.
Enroll users anytime during or after onboarding. Quickly and accurately identify locked-out account holders to allow access without human intervention. Fully compliant with BIPA, CCPA and GDPR.
On-device embedded vehicle security, entry, start and operation using face, voice and/or fingerprint. Supports Identity Proofing and driver’s license validation. Fully compliant with BIPA, CCPA and GDPR.
Instantly identify customers, detect fraud and improve UX in real time using one second of any freely spoken speech. Fully compliant with BIPA, CCPA and GDPR.
Authenticate, verify, identify and search an unlimited number of users’ faces in real time. 99.99% accurate with 0.0001% false positives. Runs on any browser, device or platform with a camera >256kB.
Authenticate, verify, identify and search an unlimited number of voices in real time. Voice identity is 96.5% accurate with 0.0001% false positives. Requires at least one second of spoken voice at 8.1kHz (telephone audio).
Authenticate, verify, identify and search an unlimited number of user’s fingerprints in real time. 99.99% accurate with 0.0001% false positives. Requires any device with at least a 2MP camera.
Ensures biometrics are only collected from a live human with minimal user inconvenience. Detects eyes open/closed, eyeglasses on/off, facial obstructions and masks, video attacks, whole video frame movement and poor lighting.
Ensures biometrics are only collected from a live human user with active user assistance. User reads a random sentence. If the user spoke the words correctly and voice identity and face identity match.
Unmatched speed & accuracy in facial, voice and fingerprint recognition algorithms. We provide 99.99% 1:Many Identification Rate (IR) at a fixed False Positive IR of 0.0001% for facial and fingerprint images for closed or open sets.
Private Identity elegantly integrates with your existing Enterprise directory using AAD, OAuth 2.0/OIDC and SAML 2.0.
Encrypted Search across unlimited private biometrics (1:Many Close-set and Open-set Identification)
100,000 encrypted searches/sec tested 2/2019 using Google Cloud AI Platform
Identification Rate (IR)
Embedding Creation Speed
Encrypted Embedding Size
False Positive Identification
False Positive Identification
False Negative Identification
False Negative Matching Rate (FNMR)
False Matching Rate (FMR)
Equal Error Rate (EER)
We actively partner with innovative technology companies to help improve current offerings, create new solutions, build the identity industry and drive new business at a global level.
"We are excited to work with Private Identity to provide private face, voice and fingerprint recognition for our clients. Their team is a pleasure to work with, our customers appreciate their advanced technology and their solutions integrate well into our architecture"
Private Identity LLC is a Washington DC-based AI/cryptography software company that provides Cloud Biometric MFA™ and Cloud Biometric Search™ to secure employee, customer and partner access across all browsers, devices and platforms in real time and absolute accuracy. The societal good achieved by solving Homomorphic Encryption is full privacy.
Our underlying technology was developed by a small group of top computer scientists and ML engineers. We converged on a solution to Homomorphic Encryption (HME) early 2018. We shared our solution with IEEE P2410 Working Group in May 2018 and subsequently helped update the IEEE 2410-2019 Standard for Biometric Open Protocol. Our first cryptography patent for HME was granted in September 2019. Additional patents are pending worldwide.
“If I have seen further it is only by standing on the shoulders of Giants.”
Mike is an entrepreneur experienced in high-growth technology ventures in biometrics, AI/ML, big data and cyber security. Prior to co-founding Private Identity, Mike served as VP and General Manager at Thomson Reuters, Executive VP and co-founder of Discovery Logic, CEO of thinkXML and CEO of Science Management Corp.
Scott is a highly regarded data scientist focused on cryptography, biometrics, AI/ML and cyber security. Scott currently leads “everything technical” at Private Identity, serves as Chair of Biometric Security for IEEE and chairs the IEEE 2410 Standard for Biometric Open Protocol. Prior to co-founding Private Identity, Scott served as CTO for a large biometrics company, was a research professor for 30 years and supported the US Government for 26 years. Scott has authored key patents and papers in machine learning, biometrics and authentication.