Urban Intelligence Platform

Intelligent Vision
for Smarter
Cities

Zurloo applies GPU-accelerated computer vision and deep learning to urban infrastructure data, delivering real-time insights on mobility, safety, and space utilisation for city planners and enterprise clients.

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Real-Time
CV Inference
GPU
Accelerated
Deep
Learning Core
VEHICLE 94% BUILDING 98% THROUGHPUT
About Zurloo

Urban Data Intelligence, Redefined

Zurloo is an India-based artificial intelligence company building a GPU-accelerated computer vision platform focused on urban environments. Founded in 2024, we develop deep learning models that process visual and spatial data at scale, transforming raw infrastructure feeds into actionable intelligence for cities and enterprises.

Our platform is designed from the ground up for high-throughput visual inference, leveraging CUDA-based parallel compute pipelines and optimised model serving to deliver low-latency insights across diverse urban data streams.

Computer Vision
Real-time object detection and scene understanding on urban feeds
Spatial Analytics
Geospatial data fusion and mobility pattern analysis
Predictive Insights
Deep learning models for demand forecasting and anomaly detection
Edge Deployment
TensorRT-optimised models for on-device and cloud-hybrid inference
ZURLOO CORE CAMERA FEEDS Urban Sensor Input CV ENGINE CUDA Accelerated SPATIAL LAYER Geospatial Fusion MODEL STORE AWS S3 + Triton INFERENCE API TensorRT Serve DASHBOARD City Planner UI
Technology

Built for Scale. Optimised for Speed.

The Zurloo Vision Engine is a full-stack deep learning platform designed for high-throughput visual inference on urban data, built on NVIDIA GPU infrastructure and cloud-native architecture.

CUDA Compute Pipeline
All model training and preprocessing runs on NVIDIA CUDA-enabled GPU clusters. Parallel compute pipelines reduce batch processing time by up to 40x compared to CPU-only workflows, enabling real-time frame analysis across multiple urban data streams simultaneously.
CUDA Parallel Processing GPU Clusters
TensorRT Optimised Inference
Deployed models are optimised using NVIDIA TensorRT to achieve low-latency inference suitable for real-time city monitoring. TensorRT layer fusion and precision calibration reduce model footprint while preserving accuracy across computer vision and object detection tasks.
TensorRT Low Latency Model Optimisation
Triton Inference Server
Model serving is handled via NVIDIA Triton Inference Server, enabling multi-model concurrent serving with dynamic batching and version management. Triton allows Zurloo to serve diverse model architectures through a single standardised endpoint, reducing infrastructure overhead.
Triton Multi-Model Serving Dynamic Batching
Computer Vision Models
Zurloo trains proprietary deep learning models for urban object detection, crowd density estimation, and traffic flow analysis. Training datasets are curated from diverse urban environments, creating data moats that support generalised performance across city geographies and conditions.
Object Detection Deep Learning Proprietary Datasets
AWS Cloud Infrastructure
Zurloo operates exclusively on Amazon Web Services for training, storage, and deployment. GPU instances handle model training workloads while S3 stores urban data archives and model artefacts. AWS serves as the primary hyperscaler supporting all inference and deployment pipelines.
AWS GPU Instances S3 Storage
Geospatial Data Fusion
Satellite imagery, aerial drone feeds, and ground-level sensor data are fused into a unified spatial model. Zurloo processes multi-modal geospatial inputs to generate enriched urban intelligence layers, combining visual data with mapping and mobility datasets for comprehensive city analytics.
Satellite Imagery Data Fusion Spatial Modelling
NVIDIA CUDA
GPU Compute
TensorRT
Inference Optimiser
Triton Server
Model Serving
Amazon Web Services
Primary Cloud
Our Team

Builders at the Intersection
of AI and Urban Systems

Zurloo is led by technologists with backgrounds in computer vision, distributed systems, and urban data science. We are a lean, focused team building for a global market from India.

[Founder Name]
Founder and Chief Executive Officer
Leads product vision, technical strategy, and business development at Zurloo. Background in applied machine learning and urban data systems.
Computer Vision Lead
Head of Engineering
Responsible for core model architecture, CUDA pipeline design, and inference optimisation. Specialises in real-time video understanding systems.
Contact

Get in Touch

Interested in deploying Zurloo's urban intelligence platform for your city or enterprise? Reach out to explore pilot programmes, technical integration, or partnership opportunities.

Website
zurloo.com
Location
India
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