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Ariadne

Precise, GDPR-compliant visitor analytics using proprietary signal-based and hybrid sensor fusion technology. Ariadne provides real-time foot traffic data, occupancy tracking, and visitor journey analytics for retail, airports, transportation hubs, and smart cities.

Their llms.txt

The beginning of the file, from our validated copy saved 2026-10-24T02:13:43.297Z. Cached copy · Source on ariadne.inc

# Ariadne

> Precise, GDPR-compliant visitor analytics using proprietary signal-based and hybrid sensor fusion technology. Ariadne provides real-time foot traffic data, occupancy tracking, and visitor journey analytics for retail, airports, transportation hubs, and smart cities.

## Core Solutions

- [People Counting](/solutions/people-counting): Hybrid Fusion technology combining Time-of-Flight and patented signal sensing for up to 99% accuracy in footfall, occupancy, dwell time, and flow tracking. Camera-free, GDPR-native, and structurally outside EU AI Act Annex III high-risk biometric categories. The pillar page covers definitions, capability triplet, technology, comparison vs cameras + Wi-Fi, accuracy by environment, how-to-choose criteria, deployment HowTo, EU AI Act stance, FAQ, and a glossary.
  - Section anchors: /solutions/people-counting/#capability (footfall, occupancy, dwell time, flow definitions), #hybrid (Hybrid Fusion technical), #compare (vs cameras and LiDAR), #choose (seven procurement criteria), #deployment (six-step rollout), #ai-act (EU AI Act stance), #faq (people counting FAQ), #glossary (term definitions).
- [Employee Scheduling](/solutions/employee-scheduling): The demand signal that retail workforce-management tools need. Anonymous footfall, dwell, and zone occupancy exported into SAP, Workday, UKG, Quinyx, or Microsoft Shifts so the schedule is built against people who walked in (not just people who bought via POS). Backs the demand-based / footfall-driven / labor-forecasting / shift-scheduling queries. Cited evidence on the page: Mani, Kesavan, Swaminathan POMS 2015 (+8.56% modeled sales lift when peak understaffing is closed), Zebra 17th Annual Global Shopper Study 2024 (in-store satisfaction 85%→81% YoY), Logile retail labor survey 2025 (77% of associates say their store loses sales to poor scheduling), McKinsey 2024 (+3pp comp-store sales correlated with lower frontline turnover).
  - Section anchors: /solutions/employee-scheduling/#definition (what employee scheduling is and how Ariadne fits as input layer, not a scheduler), #problem (four ways static scheduling leaks money, each with cited stats), #overview (three-stage process: forecast, cover, inject), #kpi (the four-stat proof moment), #integrations (SAP, Workday, UKG, Microsoft Shifts, Quinyx, plus CSV/REST fallback), #industries (retail stores, shopping centers, airports), #faq (employee scheduling FAQ including the demand-based vs forecast-based distinction and the EU AI Act compliance posture).
- [Indoor Navigation](/solutions/indoor-navigation): Privacy-first browser wayfinding for everyone, with a live blue dot once a visitor opts in. No app, no login, runs on existing Wi-Fi via EaseLink or Ariadne sensors, camera-free.
- [Visitor Marketing](/solutions/visitor-marketing): Consent-first engagement. Activates only after a visitor opts in via Wi-Fi, QR, or NFC; turns anonymous footfall into permission-based hyperlocal campaigns. GDPR, CPRA, PIPEDA complian
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Claim my listing on Agent Web Map for ariadne.inc:
1. POST https://agentwebmap.com/v1/sites/ariadne.inc/claims and keep claim_id and claim_secret private.
2. Publish the proof: add the line "AgentWebMap ownership: <token>" (token from step 1) to https://ariadne.inc/llms.txt, or use the DNS, meta-tag or well-known method the response describes.
3. POST https://agentwebmap.com/v1/sites/ariadne.inc/verify with {"claim_id": "...", "claim_secret": "..."}.
4. Save the api_key from the answer; it manages the listing (PATCH https://agentwebmap.com/v1/sites/ariadne.inc).
MCP equivalent: tools begin_ownership_claim, then verify_domain, at https://agentwebmap.com/mcp. Docs: https://agentwebmap.com/docs#verify

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