Transform Video Into Operational Intelligence
TensorForge DataPipeline converts unstructured video streams into real-time business insights using scalable edge-to-cloud AI infrastructure. Monitor inventory, optimize operations, improve safety, and uncover actionable insights from your existing camera network.
Core Value Proposition
From Unstructured Stream to Structured Data
Connect your existing camera network and immediately gain visibility into critical operational metrics without replacing hardware.
- Inventory & Stock
Monitor inventory movement and stock levels continuously with object detection and tracking.
- Foot Traffic
Analyze customer foot traffic, queue lengths, and occupancy management across facilities.
- Safety & Hazards
Ensure workplace safety compliance, detect anomalies, incidents, and potential hazards.
- Operational Efficiency
Track asset utilization and derive measurable business outcomes with cross-functional metrics.
Platform Capabilities
Enterprise-Grade Video processing
Built to handle thousands of concurrent video streams with low-latency AI inference, bridging the gap between physical operations and digital intelligence.
- Real-Time Video Processing.
- Analyze concurrent video streams with low-latency AI inference across edge devices.
- Edge-to-Cloud Architecture.
- Run AI models at the edge for rapid decision-making while synchronizing insights to the cloud.
- Computer Vision Pipeline.
- Comprehensive support for object detection, tracking, classification, segmentation, and event recognition.
- API-First Platform.
- Integrate seamlessly into ERP, WMS, CRM, security, and BI systems.
import { TensorForge } from '@tensorforge/sdk';
// Initialize the analytics pipeline
const pipeline = new TensorForge({
apiKey: process.env.TF_API_KEY,
region: 'us-east-1'
});
// Connect to RTSP stream and track
pipeline.stream('rtsp://camera-01.local/live')
.detect(['person', 'forklift'])
.onEvent('proximity_alert', (event) => {
console.log(`Hazard detected: ${event.confidence}%`);
triggerSafetyProtocol(event);
});Infrastructure
Cloud-Native Architecture
Engineered for high availability, our distributed systems leverage the best of AWS to bring insights from the edge to your dashboard.
Edge AI & Ingestion
Edge AI Processing Nodes pre-process and compress streams, sending data via Real-Time Video Ingestion Layer to Amazon Kinesis Video Streams.
Processing & Models
Distributed CV Services running on Amazon EKS communicate via Event Streaming Infrastructure. Models are served rapidly via Amazon SageMaker.
Analytics & APIs
Insights are stored in Amazon DynamoDB and Analytics Data Lake (Amazon S3), indexed by OpenSearch, and accessed through robust APIs and Dashboards.
Trusted by Industry Leaders
Scalable intelligence for diverse operational environments.
Ready to transform your physical operations?
Join the enterprises already using TensorForge DataPipeline to make faster decisions and improve measurable outcomes.