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fazeZEROApplication Atlas

Demo listing. This page uses illustrative seed metadata to demonstrate the Atlas. Claims shown here are not verified product facts.

CurbCache

Operates an edge information system for intelligent IoV—caching, compute offload, and edge AI—so vehicles meet sub-100 ms perception, HD…

Operates an edge information system for intelligent IoV—caching, compute offload, and edge AI—so vehicles meet sub-100 ms perception, HD mapping, and localization needs without exhausting onboard power or waiting on distant clouds.

DemoDeployment-Ready FoundationfazeZERO VerifiedProprietaryInternet of Things & Edge

Last verified 15 Sept 2026 · Updated 23 Sept 2026 · Metadata v4

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Configuration + implementation engagement

Problem

AV/ADAS programs and smart-mobility operators facing TB/h sensor floods (Intel ~4,000 GB/car/day) where onboard GPUs kill range and cloud RTT exceeds safety latency.

Outcome

A deployment-ready foundation that teams can configure into production.

Who uses it

  • Operations Analyst
  • Solution Architect

Key capabilities

  • Core workflow

    AI-assistedIncluded

    Primary operating workflow for this foundation.

  • Document intelligence

    AI-assistedIncluded

    Extract and ground decisions from operating documents.

Typical workflow

Primary operating flow

Trigger: An operator starts the primary use case

  1. Task

    Stage 1: Capture inputs

    Operator

  2. AI-assisted

    Stage 2: Assist with draft

    System

  3. Human checkpoint

    Stage 3: Human approval

    Approver

Task Automated AI-assisted Human checkpoint Decision

About this foundation

Vehicular edge information system (EIS). Paper argues V2V/V2I and IoV enable safety and city services, but onboard storage/compute and cloud latency both fail; EIS at radio edges provides caching, MEC, and edge AI for perception, HD mapping, and SLAM—Vehicle-as-Client and Vehicle-as-Server patterns, cooperative perception.

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