165 lines
5.7 KiB
PHP
165 lines
5.7 KiB
PHP
<?php include("head.php"); ?>
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<!-- ══ SECTION HTML ══ -->
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<div class="mt-section" id="mt-miletruth">
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<!-- Stats Banner -->
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<div class="mt-banner">
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<div class="mt-stat">
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<span class="mt-stat-num" data-target="4" data-suffix="-6hrs">0</span>
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<span class="mt-stat-label">Advance Warning</span>
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</div>
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<div class="mt-stat">
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<span class="mt-stat-num" data-target="98" data-suffix="%">0</span>
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<span class="mt-stat-label">ETA Accuracy</span>
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</div>
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<div class="mt-stat">
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<span class="mt-stat-num" data-target="50" data-suffix="+">0</span>
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<span class="mt-stat-label">Data Variables</span>
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</div>
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<div class="mt-stat">
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<span class="mt-stat-num" data-target="30" data-suffix="%">0</span>
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<span class="mt-stat-label">Exception Reduction</span>
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</div>
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</div>
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<!-- Body -->
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<div class="mt-body">
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<!-- Header -->
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<div class="mt-header">
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<div class="mt-eyebrow">AI Intelligence</div>
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<h2 class="mt-title">Why <em>MileTruth</em><sup>™</sup> is Different</h2>
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<p class="mt-desc">Unlike generic AI tools, MileTruth™ is trained exclusively on logistics data — millions of deliveries, routes, exceptions, and outcomes. It thinks like a logistics expert because it was built to be one.</p>
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</div>
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<!-- Feature Cards -->
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<div class="mt-grid">
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<!-- 1 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<path d="M10.29 3.86L1.82 18a2 2 0 001.71 3h16.94a2 2 0 001.71-3L13.71 3.86a2 2 0 00-3.42 0z"/>
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<line x1="12" y1="9" x2="12" y2="13"/>
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<line x1="12" y1="17" x2="12.01" y2="17"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Predictive Delay Detection</h5>
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<p class="mt-card-desc">AI analyses 50+ variables to predict delays 4–6 hours before they occur, giving you time to act.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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<!-- 2 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<circle cx="12" cy="12" r="3"/>
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<path d="M19.07 4.93a10 10 0 010 14.14M4.93 4.93a10 10 0 000 14.14"/>
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<path d="M15.54 8.46a5 5 0 010 7.07M8.46 8.46a5 5 0 000 7.07"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Smart Route Optimisation</h5>
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<p class="mt-card-desc">Real-time traffic, weather, and capacity data feed into dynamic routing that adapts on the fly.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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<!-- 3 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<circle cx="12" cy="12" r="10"/>
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<polyline points="12 6 12 12 16 14"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Accurate ETA Predictions</h5>
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<p class="mt-card-desc">Machine learning models trained on millions of deliveries provide 98% accurate arrival times.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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<!-- 4 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<polyline points="22 12 18 12 15 21 9 3 6 12 2 12"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Exception Management</h5>
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<p class="mt-card-desc">Automatic escalation protocols trigger when deliveries deviate from expected patterns.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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<!-- 5 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<line x1="18" y1="20" x2="18" y2="10"/>
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<line x1="12" y1="20" x2="12" y2="4"/>
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<line x1="6" y1="20" x2="6" y2="14"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Performance Analytics</h5>
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<p class="mt-card-desc">Deep insights into carrier performance, route efficiency, and cost optimisation opportunities.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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<!-- 6 -->
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<div class="mt-card">
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<div class="mt-card-icon">
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<svg viewBox="0 0 24 24">
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<polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"/>
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</svg>
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</div>
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<h5 class="mt-card-name">Automated Recommendations</h5>
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<p class="mt-card-desc">AI suggests carrier selection, consolidation opportunities, and capacity planning adjustments.</p>
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<div class="mt-card-tag">Learn More</div>
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</div>
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</div><!-- /mt-grid -->
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</div><!-- /mt-body -->
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</div><!-- /mt-section -->
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<script>
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(function () {
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var section = document.getElementById('mt-miletruth');
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if (!section) return;
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var fired = false;
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function activate() {
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if (fired) return;
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fired = true;
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section.classList.add('mt-live');
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animateCounters();
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}
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/* ── counter animation ── */
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function animateCounters() {
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section.querySelectorAll('.mt-stat-num[data-target]').forEach(function (el) {
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var target = parseInt(el.dataset.target, 10);
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var suffix = el.dataset.suffix || '';
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var start = performance.now();
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var dur = 1600;
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function tick(now) {
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var p = Math.min((now - start) / dur, 1);
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var ease = 1 - Math.pow(2, -10 * p);
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var val = Math.round(ease * target);
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el.textContent = val + suffix;
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if (p < 1) requestAnimationFrame(tick);
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}
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requestAnimationFrame(tick);
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});
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}
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if ('IntersectionObserver' in window) {
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var io = new IntersectionObserver(function (entries) {
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entries.forEach(function (e) { if (e.isIntersecting) { activate(); io.unobserve(e.target); } });
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}, { threshold: 0.1 });
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io.observe(section);
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}
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setTimeout(activate, 380);
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})();
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</script>
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