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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.

FloorPilot

Smart-building indoor localization service that learns BLE fingerprint policies from sparse user-confirmed labels plus abundant unlabeled…

A smart-building indoor localization service that learns BLE fingerprint policies from sparse user-confirmed labels plus abundant unlabeled RSSI, so campuses stop surveying every square meter to keep wayfinding accurate.

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

Mid-size campuses, museums, and corporate buildings already deploying iBeacon/BLE beacons that cannot afford continuous supervised fingerprint campaigns.

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

Semi-supervised localization ops — not another fingerprint database. The source shows deep reinforcement learning with a VAE inference engine that consumes unlabeled RSSI to generalize policies, cutting distance-to-target error ~23% and more than doubling rewards versus supervised-only DRL.

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