feat: Passwordless cross-device authentication

- Arkitektur: docs/auth/passwordless-architecture.md
- Backend: iom/quixzoom-auth-service/ (FastAPI + Redis)
- Webb: quixzoom-market-pages/se/login/ (QR-kod + polling)
- App: iom/quixzoom-app/src/features/auth/ (push + deep links)

Flöde: QR-kod → app-godkännande → webb-inloggad
This commit is contained in:
Bernt
2026-07-07 07:11:50 +00:00
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<span>France</span>
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<section class="lv-hero">
<div class="lv-hero-eyebrow">Retail Intelligence — France</div>
<h1>Retail Intelligence in France</h1>
<p class="lv-hero-subtitle">French retail markets are undergoing structural transformation, with centre-ville pedestrianisation programmes coexisting alongside continued retail park expansion. Landvex provides property investors, retailers, and Agences de developpement with field-verified intelligence to distinguish performing locations from distressed ones before capital is committed.</p>
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<div class="section-label">Capabilities</div>
<h2 class="section-title">Retail Intelligence in France — what Landvex delivers</h2>
<p class="section-sub">Every engagement is anchored to a specific decision. Select a capability to discuss how Landvex applies it to your context.</p>
<div class="use-case-grid">
<a class="use-case-card" href="/contact/">
<span class="uc-icon">&#965050</span>
<h3>Centre-Ville Retail Assessment</h3>
<p>Field-verified assessment of French town centre retail performance: occupier mix, vacancy indicators, pedestrian environment quality, and competition from periurban formats. Evidence for Action Coeur de Ville investment decisions.</p>
<div>Learn more &rarr;</div>
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<span class="uc-icon">&#9632;</span>
<h3>Zone Commerciale Monitoring</h3>
<p>Monitor condition, occupancy, and competitive dynamics across zones commerciales and centres commerciaux throughout French markets. Detect structural distress before official data captures it.</p>
<div>Learn more &rarr;</div>
</a>
<a class="use-case-card" href="/contact/">
<span class="uc-icon">&#9670;</span>
<h3>SCPI and OPCI Portfolio Intelligence</h3>
<p>Systematic field-verified monitoring of retail asset portfolios for French SCPI, OPCI, and institutional investors. Physical condition, occupier quality, and competitive positioning quantified at portfolio scale.</p>
<div>Learn more &rarr;</div>
</a></div>
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<!-- COMPARISON TABLE -->
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<div class="section-label">Comparison</div>
<h2 class="section-title">Landvex vs traditional retail intelligence methods</h2>
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<table class="comparison-table">
<thead>
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<th>Dimension</th>
<th>Traditional approach</th>
<th>Landvex</th>
</tr>
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<tbody>
<tr>
<td>Data source</td>
<td>PROCOS/CNCC surveys, modelled</td>
<td>Continuous field observation</td>
</tr>
<tr>
<td>Vacancy lag</td>
<td>612 months</td>
<td>Days</td>
</tr>
<tr>
<td>Centre-ville vs zone commerciale comparison</td>
<td>Separate surveys</td>
<td>Integrated field assessment</td>
</tr>
<tr>
<td>Physical environment quality</td>
<td>Not captured</td>
<td>Field-verified street-level</td>
</tr>
<tr>
<td>Geographic coverage</td>
<td>Selected centres</td>
<td>Any French retail location</td>
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<td>Not standard</td>
<td>Automated AI</td>
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<h2 class="section-title">Decisions Landvex informs in France</h2>
<p class="section-sub">Every Landvex engagement is anchored to one or more of these decisions. We start with your question before designing the intelligence mission.</p>
<div class="decisions-grid">
<div class="decision-chip">
<span class="chip-dot"></span>
<span>Retail property acquisition and lease negotiation</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>Action Coeur de Ville investment evidence</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>SCPI and OPCI portfolio monitoring</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>Retailer site selection intelligence</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>Urban retail planning evidence for collectivités</span>
</div></div>
</div>
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<!-- CONTRADICTION ENGINE -->
<section class="contradiction-bg">
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<h2 class="section-title">Most systems confirm what you already believe.<br>Landvex finds what doesn&rsquo;t add up.</h2>
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</div>
<div class="contradiction-box">
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<span class="conflict-flag">&#9888;</span>
<div>
<div class="conflict-title">Narrative Conflict Detected &mdash; Rue de la Republique — Lyon</div>
<div class="conflict-desc">PROCOS vacancy data indicates moderate performance. Field observation reveals effective vacancy nearly three times the reported rate across the monitored stretch.</div>
</div>
</div>
<div class="conflict-grid">
<div class="conflict-side conflict-official">
<div class="conflict-side-label">Official narrative</div>
<ul><li>&#100003 Vacancy rate: 8.4% (PROCOS Q2)</li>
<li>&#100003 Pedestrianisation programme: improving footfall</li>
<li>&#100003 No exceptional distress signals in planning register</li></ul>
</div>
<div class="conflict-side conflict-observed">
<div class="conflict-side-label">Observed reality</div>
<ul><li>&#100007 Active vacancy on 17 of 71 units — effective rate 23.9%</li>
<li>&#100007 Pop-up and temporary units masking structural vacancy on 5 units</li>
<li>&#100007 Two anchor occupiers with reduced opening hours and degraded fit-out</li>
<li>&#100007 Street environment maintenance below prime standard on 40% of frontage</li></ul>
</div>
</div>
<div class="conflict-footer">
<span class="conflict-footer-label">Confidence in official narrative</span>
<span class="conflict-confidence">20%</span>
</div>
</div>
<div>
<div>
<div>&#128269;</div>
<h4>Show me what I am missing</h4>
<p>Blind spots absent from official data and internal reports</p>
</div>
<div>
<div>&#9878;</div>
<h4>AI Red Team</h4>
<p>Every conclusion is challenged by a second model before delivery</p>
</div>
<div>
<div>&#128208;</div>
<h4>Which assumptions are wrong?</h4>
<p>Identify where your thesis conflicts with observed reality</p>
</div>
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<h2>Request a pilot for Retail Intelligence in France</h2>
<p>Tell us the decision you need to make. We will design an intelligence mission and return field-verified data within 72 hours — no procurement delay, no physical access required.</p>
<a class="lv-btn lv-btn--lg" href="/pilot/">Request a pilot &rarr;</a>
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<p class="lv-disclaimer">Intelligence outputs are indicative and advisory only. Based on field observations — not investment, financial, or legal advice. Landvex AB accepts no liability for decisions made based on these outputs. <a href="/methodology/">Methodology &rarr;</a></p>
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<span>Germany</span>
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<div class="lv-hero-eyebrow">Retail Intelligence — Germany</div>
<h1>Retail Intelligence in Germany</h1>
<p class="lv-hero-subtitle">German retail real estate markets are navigating structural shifts in consumer behaviour, with inner-city Einkaufsstrassen and retail parks facing divergent trajectories. Landvex delivers field-verified intelligence to support acquisition, leasing, and asset management decisions based on observed market reality.</p>
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<h2 class="section-title">Retail Intelligence in Germany — what Landvex delivers</h2>
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<span class="uc-icon">&#965050</span>
<h3>Innenstadt Retail Location Assessment</h3>
<p>Field-verified assessment of German Innenstadt retail performance: occupier mix, vacancy rate, pedestrian environment quality, and physical asset condition. Evidence-based input for 1A-Lage and secondary location decisions.</p>
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<h3>Fachmarktzentrum Monitoring</h3>
<p>Monitor condition, occupancy, and competitive positioning of Fachmarktzentren and retail parks across German markets. Identify deterioration trends and structural vacancy before official surveys capture them.</p>
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<span class="uc-icon">&#9670;</span>
<h3>Retail Portfolio Due Diligence</h3>
<p>Systematic field-verified assessment of retail asset portfolios for German institutional investors and open-ended funds. Occupier presentation standards, physical condition, and competitive environment quantified at scale.</p>
<div>Learn more &rarr;</div>
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<h2 class="section-title">Landvex vs traditional retail intelligence methods</h2>
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<th>Dimension</th>
<th>Traditional approach</th>
<th>Landvex</th>
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<td>Data source</td>
<td>HDE/Comfort annual surveys</td>
<td>Continuous field observation</td>
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<td>Vacancy detection latency</td>
<td>612 month statistical lag</td>
<td>Days</td>
</tr>
<tr>
<td>1A-Lage verification</td>
<td>Agent opinion, desktop</td>
<td>Field-verified observation</td>
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<td>Physical condition data</td>
<td>Not captured in standard surveys</td>
<td>Systematic street-level assessment</td>
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<td>Coverage</td>
<td>Top-50 cities only</td>
<td>Any German retail location</td>
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<td>Not standard</td>
<td>Automated AI cross-reference</td>
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<span>Innenstadt revitalisation investment planning</span>
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<div class="conflict-title">Narrative Conflict Detected &mdash; Zeil — Frankfurt am Main</div>
<div class="conflict-desc">BulwienGesa vacancy classification suggests prime performance. Field observation reveals effective vacancy three times the reported rate and occupier quality consistent with secondary location.</div>
</div>
</div>
<div class="conflict-grid">
<div class="conflict-side conflict-official">
<div class="conflict-side-label">Official narrative</div>
<ul><li>&#100003 Vacancy rate: 6.1% (BulwienGesa Q4)</li>
<li>&#100003 Footfall trend: recovering post-pandemic</li>
<li>&#100003 1A-Lage classification: maintained</li></ul>
</div>
<div class="conflict-side conflict-observed">
<div class="conflict-side-label">Observed reality</div>
<ul><li>&#100007 Active vacancy on 14 of 62 units — effective rate 22.6%</li>
<li>&#100007 Six units operating as temporary or charity lets masking structural vacancy</li>
<li>&#100007 Four anchor occupiers showing evidence of lease-end reduction in fit-out investment</li>
<li>&#100007 Street environment maintenance at B-Lage standard on central 300m stretch</li></ul>
</div>
</div>
<div class="conflict-footer">
<span class="conflict-footer-label">Confidence in official narrative</span>
<span class="conflict-confidence">16%</span>
</div>
</div>
<div>
<div>
<div>&#128269;</div>
<h4>Show me what I am missing</h4>
<p>Blind spots absent from official data and internal reports</p>
</div>
<div>
<div>&#9878;</div>
<h4>AI Red Team</h4>
<p>Every conclusion is challenged by a second model before delivery</p>
</div>
<div>
<div>&#128208;</div>
<h4>Which assumptions are wrong?</h4>
<p>Identify where your thesis conflicts with observed reality</p>
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<p class="lv-disclaimer">Intelligence outputs are indicative and advisory only. Based on field observations — not investment, financial, or legal advice. Landvex AB accepts no liability for decisions made based on these outputs. <a href="/methodology/">Methodology &rarr;</a></p>
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<span>Netherlands</span>
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<div class="lv-hero-eyebrow">Retail Intelligence — Netherlands</div>
<h1>Retail Intelligence in the Netherlands</h1>
<p class="lv-hero-subtitle">Dutch retail markets face structural oversupply in secondary and tertiary winkelgebieden, while prime inner-city locations in Amsterdam, Rotterdam, and Utrecht remain contested. Landvex delivers field-verified intelligence to distinguish genuine performing locations from those artificially supported by short-term measures.</p>
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<h2 class="section-title">Retail Intelligence in the Netherlands — what Landvex delivers</h2>
<p class="section-sub">Every engagement is anchored to a specific decision. Select a capability to discuss how Landvex applies it to your context.</p>
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<span class="uc-icon">&#965050</span>
<h3>Winkelgebied Performance Assessment</h3>
<p>Field-verified assessment of Dutch winkelgebieden: occupier mix, vacancy indicators, physical environment quality, and competitive dynamics. Evidence-based input for acquisition, lease negotiation, and disposal decisions.</p>
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<span class="uc-icon">&#9632;</span>
<h3>Retail Vacancy Monitoring</h3>
<p>Continuous monitoring of retail vacancy across Dutch town centres and retail parks. Detect emerging distress patterns before Locatus or Retailinsider annual surveys capture them.</p>
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<span class="uc-icon">&#9670;</span>
<h3>Institutional Portfolio Intelligence</h3>
<p>Systematic field-verified monitoring of retail portfolios for Dutch institutional investors, pension funds, and listed vehicles. Physical condition, occupier presentation, and competitive environment quantified at scale.</p>
<div>Learn more &rarr;</div>
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<h2 class="section-title">Landvex vs traditional retail intelligence methods</h2>
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<th>Dimension</th>
<th>Traditional approach</th>
<th>Landvex</th>
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<td>Data source</td>
<td>Locatus/Retailinsider annual</td>
<td>Continuous field observation</td>
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<td>Vacancy detection latency</td>
<td>612 month survey lag</td>
<td>Days</td>
</tr>
<tr>
<td>Physical environment assessment</td>
<td>Not captured</td>
<td>Field-verified street-level</td>
</tr>
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<td>Pop-up and temp use classification</td>
<td>Counted as occupied</td>
<td>Separately classified</td>
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<td>National sample centres</td>
<td>Any Dutch retail location</td>
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<td>Not standard</td>
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<h2 class="section-title">Decisions Landvex informs in the Netherlands</h2>
<p class="section-sub">Every Landvex engagement is anchored to one or more of these decisions. We start with your question before designing the intelligence mission.</p>
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<div class="conflict-title">Narrative Conflict Detected &mdash; Lijnbaan — Rotterdam</div>
<div class="conflict-desc">Locatus vacancy data indicates healthy market performance. Field observation reveals effective vacancy nearly three times the reported rate across the monitored street.</div>
</div>
</div>
<div class="conflict-grid">
<div class="conflict-side conflict-official">
<div class="conflict-side-label">Official narrative</div>
<ul><li>&#100003 Locatus vacancy: 7.8%</li>
<li>&#100003 Pedestrian footfall: stable year-on-year</li>
<li>&#100003 No structural distress in gemeentelijk monitor</li></ul>
</div>
<div class="conflict-side conflict-observed">
<div class="conflict-side-label">Observed reality</div>
<ul><li>&#100007 Active structural vacancy on 13 of 58 units — effective rate 22.4%</li>
<li>&#100007 4 pop-up units and 2 charity shops masking structural vacancy</li>
<li>&#100007 Two anchor occupiers showing fit-out disinvestment consistent with lease-end</li>
<li>&#100007 Public realm condition below Centrum-standard on three block frontages</li></ul>
</div>
</div>
<div class="conflict-footer">
<span class="conflict-footer-label">Confidence in official narrative</span>
<span class="conflict-confidence">18%</span>
</div>
</div>
<div>
<div>
<div>&#128269;</div>
<h4>Show me what I am missing</h4>
<p>Blind spots absent from official data and internal reports</p>
</div>
<div>
<div>&#9878;</div>
<h4>AI Red Team</h4>
<p>Every conclusion is challenged by a second model before delivery</p>
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<div>
<div>&#128208;</div>
<h4>Which assumptions are wrong?</h4>
<p>Identify where your thesis conflicts with observed reality</p>
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<h2>Request a pilot for Retail Intelligence in the Netherlands</h2>
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<p class="lv-disclaimer">Intelligence outputs are indicative and advisory only. Based on field observations — not investment, financial, or legal advice. Landvex AB accepts no liability for decisions made based on these outputs. <a href="/methodology/">Methodology &rarr;</a></p>
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<span>Sweden</span>
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<div class="lv-hero-eyebrow">Retail Intelligence — Sweden</div>
<h1>Retail Intelligence in Sweden</h1>
<p class="lv-hero-subtitle">Landvex provides Swedish property investors, retail occupiers, and municipal planners with field-verified intelligence on retail location quality, competitive dynamics, and physical environment conditions — observed at street level rather than modelled from secondary data.</p>
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<h2 class="section-title">Retail Intelligence in Sweden — what Landvex delivers</h2>
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<span class="uc-icon">&#965050</span>
<h3>Retail Location Assessment</h3>
<p>Field-verified assessment of Swedish retail locations: pedestrian environment quality, competitive positioning, retail mix, vacancy indicators, and physical access. Evidence-based input for lease negotiation and portfolio decisions.</p>
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<h3>Vacancy and Displacement Monitoring</h3>
<p>Monitor retail vacancy patterns across Swedish town centres and retail parks. Identify emerging distress signals — boarding, fascia removal, reduced signage — before they appear in official statistics.</p>
<div>Learn more &rarr;</div>
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<span class="uc-icon">&#9670;</span>
<h3>Portfolio Condition Intelligence</h3>
<p>Systematic condition monitoring of retail asset portfolios across Swedish property markets. Identify deterioration trends, maintenance requirements, and presentation standards for investor-grade asset reporting.</p>
<div>Learn more &rarr;</div>
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<th>Dimension</th>
<th>Traditional approach</th>
<th>Landvex</th>
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<tbody>
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<td>Data freshness</td>
<td>Annual surveys or modelled data</td>
<td>Continuous field observation</td>
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<td>Vacancy detection latency</td>
<td>Official statistics (612 month lag)</td>
<td>Days</td>
</tr>
<tr>
<td>Physical environment assessment</td>
<td>Desktop modelling only</td>
<td>Field-verified street-level</td>
</tr>
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<td>Competitive context</td>
<td>Category data only</td>
<td>Observed occupier-by-occupier</td>
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<td>Coverage breadth</td>
<td>Major centres only</td>
<td>Town centres to retail parks</td>
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<!-- CONTRADICTION ENGINE -->
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<div class="conflict-title">Narrative Conflict Detected &mdash; Drottninggatan — Stockholm</div>
<div class="conflict-desc">Official BID vacancy data indicates healthy centre performance. Field observation reveals a structural vacancy rate five times the reported figure.</div>
</div>
</div>
<div class="conflict-grid">
<div class="conflict-side conflict-official">
<div class="conflict-side-label">Official narrative</div>
<ul><li>&#100003 Vacancy rate: 4.2% (official BID survey, Q3)</li>
<li>&#100003 Footfall index: stable year-on-year</li>
<li>&#100003 No exceptional distress signals in planning data</li></ul>
</div>
<div class="conflict-side conflict-observed">
<div class="conflict-side-label">Observed reality</div>
<ul><li>&#100007 Active vacancy on 11 of 48 units — effective rate 23%</li>
<li>&#100007 Temporary lets and pop-ups masking structural vacancy on 4 units</li>
<li>&#100007 Three anchor occupiers have reduced fit-out quality significantly</li>
<li>&#100007 Pedestrian environment maintenance below investment-grade standard</li></ul>
</div>
</div>
<div class="conflict-footer">
<span class="conflict-footer-label">Confidence in official narrative</span>
<span class="conflict-confidence">15%</span>
</div>
</div>
<div>
<div>
<div>&#128269;</div>
<h4>Show me what I am missing</h4>
<p>Blind spots absent from official data and internal reports</p>
</div>
<div>
<div>&#9878;</div>
<h4>AI Red Team</h4>
<p>Every conclusion is challenged by a second model before delivery</p>
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<div>
<div>&#128208;</div>
<h4>Which assumptions are wrong?</h4>
<p>Identify where your thesis conflicts with observed reality</p>
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<h2>Request a pilot for Retail Intelligence in Sweden</h2>
<p>Tell us the decision you need to make. We will design an intelligence mission and return field-verified data within 72 hours — no procurement delay, no physical access required.</p>
<a class="lv-btn lv-btn--lg" href="/pilot/">Request a pilot &rarr;</a>
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<p class="lv-disclaimer">Intelligence outputs are indicative and advisory only. Based on field observations — not investment, financial, or legal advice. Landvex AB accepts no liability for decisions made based on these outputs. <a href="/methodology/">Methodology &rarr;</a></p>
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<span>United Kingdom</span>
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<!-- HERO -->
<section class="lv-hero">
<div class="lv-hero-eyebrow">Retail Intelligence — United Kingdom</div>
<h1>Retail Intelligence in the United Kingdom</h1>
<p class="lv-hero-subtitle">UK retail real estate continues to undergo structural adjustment, with high street vacancy remaining above long-term averages and out-of-town retail formats facing divergent performance trajectories. Landvex provides field-verified intelligence to support acquisition, asset management, and place-making decisions based on observed reality rather than survey interpolation.</p>
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<div class="section-label">Capabilities</div>
<h2 class="section-title">Retail Intelligence in the United Kingdom — what Landvex delivers</h2>
<p class="section-sub">Every engagement is anchored to a specific decision. Select a capability to discuss how Landvex applies it to your context.</p>
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<span class="uc-icon">&#965050</span>
<h3>High Street Vacancy Monitoring</h3>
<p>Field-verified vacancy monitoring across UK town centres and high streets. Identify structural vacancy, temporary uses masking distress, and deterioration in occupier quality — updated continuously, not on annual survey cycles.</p>
<div>Learn more &rarr;</div>
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<span class="uc-icon">&#9632;</span>
<h3>Retail Park and Shopping Centre Assessment</h3>
<p>Systematic field assessment of UK retail park and shopping centre assets: occupier mix, physical condition, presentation standards, and competitive positioning. Evidence for institutional acquisition and disposal decisions.</p>
<div>Learn more &rarr;</div>
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<a class="use-case-card" href="/contact/">
<span class="uc-icon">&#9670;</span>
<h3>Local Authority Place Intelligence</h3>
<p>Support UK local authorities in monitoring high street health for BID management, Levelling Up Fund interventions, and UKSPF programme targeting. Field-verified evidence to underpin investment business cases.</p>
<div>Learn more &rarr;</div>
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<div class="section-label">Comparison</div>
<h2 class="section-title">Landvex vs traditional retail intelligence methods</h2>
<p class="section-sub">How field-verified continuous intelligence compares to conventional survey and inspection approaches.</p>
<table class="comparison-table">
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<th>Dimension</th>
<th>Traditional approach</th>
<th>Landvex</th>
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<td>Data source</td>
<td>LDC/Springboard annual surveys</td>
<td>Continuous field observation</td>
</tr>
<tr>
<td>Vacancy detection latency</td>
<td>612 month survey lag</td>
<td>Days</td>
</tr>
<tr>
<td>Physical condition capture</td>
<td>Not in standard footfall data</td>
<td>Systematic street-level assessment</td>
</tr>
<tr>
<td>Pop-up and temporary use detection</td>
<td>Counted as occupied</td>
<td>Flagged and classified separately</td>
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<tr>
<td>Coverage</td>
<td>Monitored centres only</td>
<td>Any UK retail location</td>
</tr>
<tr>
<td>Contradiction detection</td>
<td>Not standard</td>
<td>Automated AI cross-reference</td>
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<div class="section-label">Decision support</div>
<h2 class="section-title">Decisions Landvex informs in the United Kingdom</h2>
<p class="section-sub">Every Landvex engagement is anchored to one or more of these decisions. We start with your question before designing the intelligence mission.</p>
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<span>UK retail property acquisition due diligence</span>
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<span>REIT and fund portfolio monitoring</span>
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<div class="decision-chip">
<span class="chip-dot"></span>
<span>Local authority high street intervention evidence</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>BID renewal and investment business case</span>
</div>
<div class="decision-chip">
<span class="chip-dot"></span>
<span>Retailer UK site selection intelligence</span>
</div></div>
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<!-- CONTRADICTION ENGINE -->
<section class="contradiction-bg">
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<div>
<div class="section-label">Contradiction Engine</div>
<h2 class="section-title">Most systems confirm what you already believe.<br>Landvex finds what doesn&rsquo;t add up.</h2>
<p class="section-sub">The most actionable intelligence is contradiction. Landvex actively searches for conflicts between official narratives and observed field reality — and quantifies the confidence gap.</p>
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<div class="contradiction-box">
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<span class="conflict-flag">&#9888;</span>
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<div class="conflict-title">Narrative Conflict Detected &mdash; Market Street — Manchester City Centre</div>
<div class="conflict-desc">LDC data and BID assessment indicate moderate recovery. Field observation reveals effective structural vacancy more than twice the reported rate.</div>
</div>
</div>
<div class="conflict-grid">
<div class="conflict-side conflict-official">
<div class="conflict-side-label">Official narrative</div>
<ul><li>&#100003 LDC vacancy rate: 11.3%</li>
<li>&#100003 Footfall index: improving trend</li>
<li>&#100003 BID health assessment: stable</li></ul>
</div>
<div class="conflict-side conflict-observed">
<div class="conflict-side-label">Observed reality</div>
<ul><li>&#100007 Active structural vacancy on 19 of 74 units — effective rate 25.7%</li>
<li>&#100007 7 pop-up, temporary, and charity units offsetting structural vacancy</li>
<li>&#100007 Three former anchor units subdivided or at reduced rental value</li>
<li>&#100007 Public realm maintenance below investment-grade standard on main frontage</li></ul>
</div>
</div>
<div class="conflict-footer">
<span class="conflict-footer-label">Confidence in official narrative</span>
<span class="conflict-confidence">14%</span>
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</div>
<div>
<div>
<div>&#128269;</div>
<h4>Show me what I am missing</h4>
<p>Blind spots absent from official data and internal reports</p>
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<div>
<div>&#9878;</div>
<h4>AI Red Team</h4>
<p>Every conclusion is challenged by a second model before delivery</p>
</div>
<div>
<div>&#128208;</div>
<h4>Which assumptions are wrong?</h4>
<p>Identify where your thesis conflicts with observed reality</p>
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<h2>Request a pilot for Retail Intelligence in the United Kingdom</h2>
<p>Tell us the decision you need to make. We will design an intelligence mission and return field-verified data within 72 hours — no procurement delay, no physical access required.</p>
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<p class="lv-disclaimer">Intelligence outputs are indicative and advisory only. Based on field observations — not investment, financial, or legal advice. Landvex AB accepts no liability for decisions made based on these outputs. <a href="/methodology/">Methodology &rarr;</a></p>
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