1. Overview

AITiqs is a next-generation AI incident management platform that uses video intelligence to detect, analyze, and prioritize real-world incidents in construction sites, warehouses, factories, and other high-risk environments.

Built on AWS Bedrock and AWS Lambda, AITiqs ingests video frames or event clips, identifies safety and operational incidents using AI models, classifies their severity, and automatically triggers notifications or workflows — all in real time and at scale

2. Core Concept

AITiqs transforms raw camera output into actionable safety insights.

For example:

• Detect a worker without a helmet or vest
• Identify unsafe proximity to heavy machinery
• Detect smoke, fire, or chemical spills
• Recognize unauthorized entry zones or loitering
• Monitor slips, falls, and collisions

Each detected event is evaluated by an AI reasoning layer (via Bedrock) to assign a priority level (Critical / High / Medium / Low) and recommended response, all handled automatically via AWS serverless services

3. Target Users

• Construction & infrastructure companies
• Warehouse & logistics operators
• Manufacturing and industrial facilities
• Safety and compliance teams
• Smart city / security integrator

4. Architecture Overview (AWS-Native)

Input & Ingestion

• Amazon Kinesis Video Streams (KVS) or RTSP streams from IP cameras
• AWS Lambda or AWS IoT Core for real-time event ingestion
• Optional S3 storage for archived video clip

AI Processing Layer

1. Computer Vision Detection
2. 
   
   • Run Amazon Rekognition Custom Labels or SageMaker-trained CV models (for PPE detection, motion, zone violations)
   • Output: structured incident metadata (timestamp, object type, coordinates)
3. AI Prioritization (AWS Bedrock)
4. 
   
   • Send metadata + context (incident type, zone risk level, time, frequency) to Bedrock model (Claude / Titan)
   • Bedrock returns:
   • 
     
     • Priority (Critical / High / Medium / Low)
     • Incident category (safety, security, operational)
     • Summary & rationale
     • Recommended next action (alert, pause machine, notify team)
5. Serverless Orchestration
6. 
   
   • AWS Lambda / Step Functions handle:
   • 
     
     • Routing alerts to proper channels
     • Creating tickets in ServiceNow/Jira
     • Triggering automated controls (via IoT or APIs)
   • Amazon SNS / EventBridge for alert broadcasting

Storage & Analytics

• Amazon DynamoDB for structured incident logs
• Amazon S3 for video snapshots or evidence clips
• Amazon OpenSearch / QuickSight for dashboards & trends

Notifications & Integrations

• Slack / Teams / Email / SMS (SNS)
• ServiceNow, Jira, or custom ERP integration
• Optional mobile dashboard via AWS Amplify frontend