Skip to main content

Intelligence for the Modern Landscape: Smart Cities & Buildings

Privacy-first Vision AI that turns visual data into actionable insight, at scale and on the edge.

Learn More

Modern urban environments and commercial buildings generate massive volumes of visual data. The challenge isn’t capturing it—it’s turning that data into actionable intelligence without compromising the privacy of the people within those spaces. 

AlgoFace provides a modular, edge-enabled Vision AI platform that allows planners and operators to understand movement, density, and engagement while keeping identities protected, so organizations can design safer, more efficient spaces without compromising privacy or public trust.

How We Transform Urban Environments

We bridge the gap between high-level analytics and rigorous privacy standards. Our technology seamlessly integrates into existing Cameras and VMS to deliver insights across these key pillars:

Flow, Transit & Occupancy

Understand the “pulse” of the environment. From city intersections and transit platforms to building lobbies, analyze how people move, where they congregate, and how long they wait. Use these insights to reduce congestion, optimize transit schedules, and design more intuitive physical spaces. 

Public Safety & Situational Awareness

Detect unusual crowd dynamics, high-stress environments, or safety risks in real-time. Enhance emergency preparedness without identifying individuals.

Engagement & Attention Analytics

Leverage demographic data and measure how people interact with signage, kiosks, and public venues. Gain insight into attention, alertness, and behavioral patterns—without relying on personal identity.

The Modular Approach to Smart Cities

AlgoFace supports cities with modular, edge-enabled AI tools that analyze demographic trends and crowd behavior, without storing personally identifiable information(PII) or transmitting it to the cloud. Operators are able to selectively enable analytic capabilities based on their objectives, environment, and regulatory requirements.

This modular approach allows cities and buildings to immediately integrate privacy-preserving analytics and to unlock insights as desired without redesigning infrastructure or changing governance models.

Core Technology Capabilities

1

Edge-Based Facial Redaction

The Foundation of Privacy. This capability automatically obscures identifiable facial features on inbound video feeds in real-time. By processing at the “edge” (on-site hardware), sensitive data is redacted before it ever hits a network or cloud.
  • Primary Value: Enables the use of video analytics in public and shared spaces while enhancing compliance with privacy regulations.
  • Operational Use: Pedestrian flow analysis, occupancy monitoring, and venue safety.
2

Aggregate Demographic Insights

Trend-Level Population Data. Provides high-level demographic trends using non-identifying attributes. Data is delivered in “buckets” to ensure individuals cannot be singled out.
  • Key Metrics: Estimated age ranges and gender distribution.
  • Operational Use: Urban planning, public space design, and aligning transit services with population patterns.
3

Crowd & Spatial Intelligence

High-Level Environmental Awareness. Uses de-identified signals to measure the volume and movement of people within a physical environment.
  • Density & Flow: Measures real-time people counts, crowd density, and directional movement.
  • Dwell & Wait Times: Analyzes how long individuals remain in specific zones and how they transition between them.
  • Operational Use: Urban telemetry for transit hubs, congestion detection, and staffing optimization for peak periods.
4

Behavioral & Engagement Analytics

Understanding Human Interaction. Evaluates how people interact with their surroundings by analyzing posture and orientation without capturing identity.
  • Head Pose & Orientation: Used to determine where people are looking and how they are positioned.
  • Attention Analysis: Measures gaze and engagement duration to evaluate the effectiveness of signage or kiosks.
  • Facial Expression Analysis: Extracts semantic signals (e.g., high-stress indicators) to monitor public comfort and safety.
5

Non-identified Cross Camera Tracking (Re-ID)

Longitudinal Movement Analysis. A configurable feature that links the same signal across multiple cameras.
  • The Privacy Edge: Understands repeat interactions and circulation patterns across a building, campus or station without ever needing or storing personal identities.
  • Operational Use: Analyzing complex movement patterns in large buildings or transit networks.

Start Simple. Scale Intelligently.

Designed with clear input from smart infrastructure operators, our solutions offer cities and buildings the flexibility to quickly deploy technologies that address immediate needs while also enabling easy expansion capabilities as new requirements and opportunities arise.

Privacy-First Architecture

By keeping data control with the client, enabling seamless compliance through a combination of edge-based processing, real-time redaction and data minimization, operational optimization is realized.

  • Edge-Native Deployment: All processing happens on-device or at the edge, eliminating the risks of cloud-centric databases.
  • Data Minimization: Raw video is transformed into privacy-enhanced metadata instantly; identifying data is never stored.
  • Customer-Controlled Governance: The rules, scope, and depth of analysis are defined by the customer, ensuring alignment with local policies.

The Result: Intelligence Without Intrusion

AlgoFace delivers the intelligence needed to optimize pedestrian flow, enhance public safety, and streamline operations in smart cities and buildings—all without the liability of invasive surveillance. It is high-performance, easily scalable AI designed to improve urban environments.

Build a Smarter Environment, Responsibly.

Discover how our technology supports intelligent infrastructure with unmatched flexibility and scale.

Scale Smarter Spaces