Human-centric
AI Computer Vision
3DiVi Inc., founded in 2011, is one of the leading developers of AI and machine learning (ML) technologies for computer vision.
  • Face detection and tracking in images and video

  • Face comparison and search in control lists with a face match score

  • Face identification at different angles and tilts

  • Identification of masked or partially covered faces

  • Confident detection with 20 px between pupils and identification with 30 px

  • Face liveness detection (spoofing) and photo suitability check for identification (QAA)

Face Recognition System for Large-Scale Projects

  • 50 million face vector comparisons per second

    Searching through a database of 50 million faces using 1 CPU core takes 1 second
  • ½ second for face vector creation and database search

    Image search takes ½ second for single requests and supports linear scalability up to X requests per second with horizontal server scaling
  • Unlimited number of faces in the database

    Creation and storage of a database of people (over 100,000,000) with face photos, full names, activity history, and additional free-form text fields
  • Adding cameras without expanding the system core

    For video analytics tasks, there is no need to buy a central server with extra power for future scaling, as adding cameras only requires adding video analytics servers
  • Unlimited number of cameras or video files

    Support for various camera types (IP / USB) and simultaneous multi-threaded processing of camera groups
  • External database for storing large images

    Delivered in Docker containers and deployed using Kubernetes in a local environment with the possibility of using an external database

Smooth Integration into Access Control and Video Analytics Systems

  • GraphQL API and Admin web interface

    Microservice architecture with GraphQL API via webhook and websocket

    Web interface streamlines learning and configuration of key parameters
  • Existing integrations with video surveillance and access control systems

    Partnership integrations with 4 video surveillance systems and 2 access control systems

Versatile and Adaptable Face Recognition Solution

  • Support for Ubuntu and CentOS

    Deployment support on Ubuntu 20 and CentOS 7. Video processing client can be deployed on Windows and Linux ARM
  • On-prem installation in an isolated environment

    Delivered in Docker containers and deployed using Kubernetes in a local environment
  • Deployment in Amazon EKS and Google KE cloud environments

    Deployment in Amazon EKS and Google KE environments with automatic scaling of hardware resources
  • Edge processing — recognition without sending video to the center

    Edge video stream processing prevents network congestion from high-resolution video streams

  • Neural network suite optimized for low-power devices

    Option to choose between full and optimized identification methods for mobile and low-power devices
  • Protection against photo and data leakage from the database

    With edge processing, face recognition is performed without sending video to the center, using only face templates without additional information, eliminating the risk of photo leakage

We accompany you through all 4 stages

Market analysis

Share our experience in similar business cases and highlight potentially risky areas.

Offer proven partnership solutions.

Solution selection

Assist in selecting the most suitable technological solutions and propose optimal architecture and equipment configuration.


Provide services for server capacity calculation and assessment of existing cameras' suitability.


Provide testing methodologies for effective participation in pilots.

Implementation and testing

Develop new functionality according to your requirements and ensure quick technical support through various communication channels, including messengers and email.


Conduct an assessment of the quality of face images in the database to predict the probability of identification errors and help configure system parameters to minimize errors.

Market entry

Implement the system under your brand (White Label) to simplify its promotion in the international market.


Offer a flexible licensing model or business model: profit-sharing, transaction-based, or based on the number of faces or cameras.

Services
Documentation
Support
Documentation
  • CPU: 4+ cores 3GHz AVX support
  • RAM: 24 GB
  • HDD: 100 GB
Supported OS versions
System requirements
Performance metrics

Technical Support

Testimonials

Save your development team's time and budget

3DiVi's experience shows that integrating a ready-made face recognition system into your product is 4 times faster and 10 times more cost-effective than developing your own system using SDK.

This also eliminates the risk of inefficient organization of multithreaded processing in your project.
Mike P
Project manager
$0 + 2-3 weeks — Testing and exploration
3DiVi provides a server for cloud tests, consultations, and testing materials.
Client engages employees to study the technology for 2-3 weeks.
Developing your own face recognition solution using SDK:
Required team (6-9 people):
architect, developers, analyst, QA, technical writer, manager.

  • 3-5 months — developing image processing functionality.
  • 4-6 months — developing video stream processing functionality.
  • 3-4 months — process debugging, test development, bug fixing.
  • 2-3 months — optimization for different platforms and hardware.

Fast response from SDK providers is required.
$9 500 + 2-3 months — PoC / MVP level integration
3DiVi provides a devpack with the necessary set of licenses for a year, helps deploy and configure the system for the business task, and offers technical support. Devpack costs can be refunded as a discount when purchasing licenses for a real project.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 2-3 months.
$25 000 + 3-5 months — Product level integration
3DiVi provides a devpack with the necessary set of licenses for a year, helps deploy and configure the system for the business task, offers technical support, and customizes the system for specific integration requirements. Devpack costs can be refunded as a discount when purchasing licenses for a real project or ordering new functionality.
Client purchases the devpack, hardware (own or in AWS/GKE cloud), cameras, and engages their developers for product integration for 3-5 months.
$200 000 — MVP / PoC level

5-8 months
$500 000 — Product level
12-18 months
1. Number of profiles in the database
Profile represents a person within Omni Face Recognition Platform and stores information about this person and their biometric template. Events related/not related to a particular profile are not subject to licensing.
2. Number of video streams processed by Omni Agent
When working with Omni Agent, you need to purchase licenses for the total number of video streams concurrently connected to Omni Face Recognition Platform.
3DiVi offers potential partnership opportunities providing licenses and project support with subsequent profit sharing.
  • USB licenses are available for deployment in isolated environments without Internet access.
  • Licenses can be time-limited or perpetual.
  • Omni Face Recognition Platform can be licensed based on one or multiple metrics. An unlimited license is available as an option.
Unlock the fast track "from concept to market" with 3DiVi's technologies and business logic templates.
1

Idea and market analysis

2

Selection and fine-tuning of the neural network

For over 12 years, 3DiVi AI team has developed a robust suite of neural networks, fine-tuned to boost your project without the need to maintain your own AI team.

3

SDK for neural network implementation and app development

Business app developers can't use neural networks as-is. They require adaptation for different languages (C++, Java, Python, Swift, etc.) and operating systems. 3DiVi Face SDK has already done this for you.

4

API for accelerating integration

Work with SDK typically requires specialized developers. However, with the provided API, generalist developers can handle integration, saving money on specialized developers and reducing development time. Leverage 3DiVi Face Image API and 3DiVi Omni Stream Agent.

5

Templates for business logic and scenarios

3DiVi's suite of neural networks for faces, bodies, and objects allows you to integrate ready-made business scenarios (such as facial assessments, face occlusion control, identifying people crossing the lines, etc.). By using 3DiVi Face Image API and 3DiVi Omni Stream Agent, your team can avoid spending time on these implementations.

6

Database for events accumulating and transferring to business apps

Creating your own face recognition system can be challenging, particularly with asynchronous request processing and synchronizing face lists with the SDK's search index. 3DiVi Omni Face Recognition Platform handles this for you, leaving only the UI, roles and logs to develop.

7

Business logic, interfaces, roles, integrations

Your team can concentrate on high-level tasks like implementing business logic, roles, interfaces and marketing. The foundational technology is covered by 3DiVi Omni Face Recognition Platform.

8

Market entry and monetization