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6<script> 7 const menuToggle = document.querySelector('.menu-toggle'); 8 const navLinks = document.querySelector('.nav-links'); 9 const nav = document.querySelector('nav'); 10 11 const setBodyOffset = () => { 12 if (!nav) return; 13 // Force layout recalculation to get accurate height 14 const height = nav.getBoundingClientRect().height; 15 document.body.style.paddingTop = `${height}px`; 16 }; 17 18 if (nav) { 19 // Set immediately 20 setBodyOffset(); 21 // Set after DOM fully loaded 22 if (document.readyState === 'loading') { 23 document.addEventListener('DOMContentLoaded', setBodyOffset); 24 } 25 // Set on resize 26 window.addEventListener('resize', setBodyOffset); 27 // Set after fonts load (can affect height) 28 if (document.fonts && document.fonts.ready) { 29 document.fonts.ready.then(setBodyOffset); 30 } 31 } 32 33 if (menuToggle && navLinks) { 34 menuToggle.addEventListener('click', () => { 35 navLinks.classList.toggle('is-open'); 36 menuToggle.classList.toggle('is-active'); 37 const isOpen = navLinks.classList.contains('is-open'); 38 menuToggle.setAttribute('aria-expanded', isOpen); 39 document.body.style.overflow = isOpen ? 'hidden' : ''; 40 }); 41 42 navLinks.querySelectorAll('a').forEach(link => { 43 link.addEventListener('click', () => { 44 if (navLinks.classList.contains('is-open')) { 45 navLinks.classList.remove('is-open'); 46 menuToggle.classList.remove('is-active'); 47 menuToggle.setAttribute('aria-expanded', 'false'); 48 document.body.style.overflow = ''; 49 } 50 }); 51 }); 52 } 53 54 // Enhanced scroll behavior for sticky header 55 if (nav) { 56 const prefersReducedMotion = window.matchMedia('(prefers-reduced-motion: reduce)').matches; 57 let lastScrollY = window.scrollY; 58 59 window.addEventListener('scroll', () => { 60 const currentScrollY = window.scrollY; 61 const isScrollingDown = currentScrollY > lastScrollY; 62 63 if (currentScrollY > 50) { 64 // More blur and opacity when scrolled 65 nav.style.backdropFilter = 'blur(20px)'; 66 nav.style.webkitBackdropFilter = 'blur(20px)'; 67 68 if (document.body.classList.contains('theme-bw') || document.body.classList.contains('theme-transparent')) { 69 nav.style.backgroundColor = 'rgba(11, 11, 11, 0.95)'; 70 } else { 71 nav.style.backgroundColor = 'rgba(31, 27, 48, 0.95)'; 72 } 73 74 nav.style.borderBottomColor = 'rgba(255, 255, 255, 0.15)'; 75 } else { 76 // Default blur and opacity when at top 77 nav.style.backdropFilter = 'blur(12px)'; 78 nav.style.webkitBackdropFilter = 'blur(12px)'; 79 80 if (document.body.classList.contains('theme-bw') || document.body.classList.contains('theme-transparent')) { 81 nav.style.backgroundColor = 'rgba(11, 11, 11, 0.9)'; 82 } else { 83 nav.style.backgroundColor = 'rgba(31, 27, 48, 0.85)'; 84 } 85 86 nav.style.borderBottomColor = 'rgba(255, 255, 255, 0.08)'; 87 } 88 89 // Disable transition effects for users who prefer reduced motion 90 if (prefersReducedMotion) { 91 nav.style.transition = 'none'; 92 } 93 94 lastScrollY = currentScrollY; 95 }); 96 } 97</script>
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305 <main class="container left"> <div class="hero-wrapper"> <div class="hero-content"> <h1 class="hero-code">TABULARIS.AI<span class="sr-only"> â Synthetic Data & Custom AI Models</span></h1> <p class="hero-value-prop">Need more training data? We generate it. Need a custom AI model? We build it.</p> <p class="hero-supporting">Production-ready AI, deployed on your infrastructure. Any data type. Any complexity.</p> <div class="hero-highlights" aria-label="Key trust highlights"> <span class="highlight-chip">500K+ Monthly Downloads</span> <span class="highlight-chip">On-Premise and Edge Deployment</span> </div> <div class="cta-buttons-container"> <button class="explore-button secondary-cta" onclick="window.open('https://huggingface.co/tabularisai', '_blank')" aria-label="Explore Our AI Models on HuggingFace"> 306Explore Our AI Models 307</button> </div> <!-- Trusted By Section --> <div class="hero-trusted-by"> <p class="trusted-by-label">Trusted by</p> <div class="hero-logos-container"> <a href="https://www.nvidia.com/" target="_blank" rel="noopener noreferrer" class="hero-logo-link" aria-label="NVIDIA Inception Partner"> <img src="/nvidia.webp" alt="NVIDIA" class="hero-logo"> </a> <a href="https://aws.amazon.com/" target="_blank" rel="noopener noreferrer" class="hero-logo-link" aria-label="AWS Activate Partner"> <img src="/aws.webp" alt="AWS" class="hero-logo"> </a> <a href="https://about.google/" target="_blank" rel="noopener noreferrer" class="hero-logo-link" aria-label="Google Cloud Partner"> <img src="/google.webp" alt="Google" class="hero-logo"> </a> </div> </div> </div> <div class="hero-features"> <a href="/sentiment-analysis" class="feature-item" aria-label="Learn more about the Sentiment & Emotion API"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"> <path d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z"></path> <path d="M8 12h.01"></path> <path d="M12 12h.01"></path> <path d="M16 12h.01"></path> </svg> </div> <h2 class="feature-title">Sentiment & Emotion API</h2> <p class="feature-desc">Multilingual sentiment + emotion classification in 23 languages with sub-second responses.</p> <p class="feature-outcome">â From $19/mo · free tier</p> </a> <a href="/custom-models" class="feature-item" aria-label="Learn more about Custom Models"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <rect x="4" y="4" width="16" height="16" rx="2" ry="2"></rect> <rect x="9" y="9" width="6" height="6"></rect> <line x1="9" y1="1" x2="9" y2="4"></line> <line x1="15" y1="1" x2="15" y2="4"></line> <line x1="9" y1="20" x2="9" y2="23"></line> <line x1="15" y1="20" x2="15" y2="23"></line> </svg> </div> <h2 class="feature-title">Custom Models</h2> <p class="feature-desc">Specialized AI trained from scratch for your exact use case.</p> <p class="feature-outcome">â Outperform general-purpose LLMs</p> </a> <a href="/knowledge-distillation" class="feature-item" aria-label="Learn more about Knowledge Distillation"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <polyline points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"></polyline> </svg> </div> <h2 class="feature-title">Knowledge Distillation</h2> <p class="feature-desc">Compress frontier teacher models into fast, deployable specialists.</p> <p class="feature-outcome">â 10x cheaper inference</p> </a> <a href="/deploy-anywhere" class="feature-item" aria-label="Learn more about Deploy Anywhere"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <path d="M12 2L2 7l10 5 10-5-10-5z"></path> <path d="M2 17l10 5 10-5"></path> <path d="M2 12l10 5 10-5"></path> </svg> </div> <h2 class="feature-title">Deploy Anywhere</h2> <p class="feature-desc">On-prem, VPC, or edge. No cloud, no data leaks.</p> <p class="feature-outcome">â Full data sovereignty</p> </a> <a href="/fast-data-labeling" class="feature-item" aria-label="Learn more about Fast Data Labeling"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"> <polygon points="13 2 3 14 12 14 11 22 21 10 12 10 13 2"></polygon> </svg> </div> <h2 class="feature-title">Fast Data Labeling</h2> <p class="feature-desc">Auto-label text, images, tables, time-series, and audio in hours â active learning + human review.</p> <p class="feature-outcome">â 1000à faster than manual</p> </a> <a href="/synthetic-data" class="feature-item" aria-label="Learn more about Synthetic Data"> <div class="feature-icon"> <svg width="24" height="24" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" stroke-linecap="round" stroke-linejoin="round"> <rect x="2" y="7" width="20" height="14" rx="2" ry="2"></rect> <path d="M16 21V5a2 2 0 0 0-2-2h-4a2 2 0 0 0-2 2v16"></path> </svg> </div> <h2 class="feature-title">Synthetic Data</h2> <p class="feature-desc">Generate realistic text, tabular, time-series, and image data for training.</p> <p class="feature-outcome">â GDPR-compliant by design</p> </a> </div> </div> </main> <section class="problem-solution-section"> <div class="problem-solution-content"> <div class="problem-box vision-box"> <h3 class="problem-title">Why Now?</h3> <p class="problem-text">AI projects fail because of data, not algorithms. You can't get enough training data. The data you have is too sensitive to share. Cloud APIs leak it, cost a fortune, and fail compliance audits. Meanwhile, the hardware in your office is more powerful than what trained GPT-2.</p> <p class="problem-source">The bottleneck isn't compute. It's data and sovereignty.</p> </div> <div class="solution-box"> <h3 class="solution-title">How We Do It</h3> <p class="solution-text">We generate the synthetic data you need, then build compact task-s
307pecialized models from it. They run efficiently on CPUs and affordable GPUs using advanced quantization and knowledge distillation.</p> <div class="solution-features"> <div class="solution-feature"> <svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <polyline points="20 6 9 17 4 12"></polyline> </svg> <span>Zero latency, full data sovereignty</span> </div> <div class="solution-feature"> <svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <polyline points="20 6 9 17 4 12"></polyline> </svg> <span>Up to 90% cost reduction vs. cloud APIs</span> </div> <div class="solution-feature"> <svg width="20" height="20" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2"> <polyline points="20 6 9 17 4 12"></polyline> </svg> <span>Works offline, anywhere</span> </div> </div> </div> </div> </section> <section class="offerings-section"> <div class="offerings-content"> <div class="section-header"> <h2 class="offerings-title">What We Deliver</h2> <p class="offerings-subtitle">End-to-end AI solutions, from data to deployment.</p> </div> <div class="offerings-grid"> <div class="offering-item"> <div class="offering-number">01</div> <h3 class="offering-title">Synthetic Data Generation</h3> <p class="offering-desc">Generate realistic training data across text, tabular, time-series, and images. Train AI models without exposing real data. GDPR-compliant by design.</p> <div class="offering-formats"> <span class="offering-tag">Text</span> <span class="offering-tag">Tabular</span> <span class="offering-tag">Time-Series</span> <span class="offering-tag">Images</span> </div> </div> <div class="offering-item"> <div class="offering-number">
30702</div> <h3 class="offering-title">Custom AI Models</h3> <p class="offering-desc">Specialized models trained from scratch or fine-tuned for your exact use case. From sentiment analysis to medical document processing - any complexity.</p> <div class="offering-formats"> <span class="offering-tag">NLP</span> <span class="offering-tag">Classification</span> <span class="offering-tag">Extraction</span> <span class="offering-tag">Generation</span> </div> </div> <div class="offering-item"> <div class="offering-number">03</div> <h3 class="offering-title">Deployment & Optimization</h3> <p class="offering-desc">Models deployed on your infrastructure. Quantized for speed, optimized for cost. On-prem, VPC, or edge - with full data sovereignty.</p> <div class="offering-formats"> <span class="offering-tag">On-Premise</span> <span class="offering-tag">Edge</span> <span class="offering-tag">VPC</span> <span class="offering-tag">Offline</span> </div> </div> <div class="offering-item"> <div class="offering-number">04</div> <h3 class="offering-title">Fast Data Labeling</h3> <p class="offering-desc">Auto-label text, images, tables, time-series, and audio in hours, not months. Foundation-model pre-labeling, active learning, and expert human review combined into a single rapid pipeline. <a href="/fast-data-labeling" class="offering-link">See the pipeline â</a></p> <div class="offering-formats"> <span class="offering-tag">Active Learning</span> <span class="offering-tag">Multi-modal</span> <span class="offering-tag">Human-in-the-loop</span> <span class="offering-tag">RLHF</span> </div> </div> </div> </div> </section> <section class="use-cases-section"> <div class="use-cases-content"> <div class="section-header"> <h2 class="use-cases-title">Real-world use cases</h2> <p class="use-cases-subtitle">What teams run with Tabularis today.</p> </div> <div class="use-cases-grid"> <div class="use-case-item" data-industry="sentiment"> <div class="use-case-icon"> <svg width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.5"> <path d="M21 15a2 2 0 0 1-2 2H7l-4 4V5a2 2 0 0 1 2-2h14a2 2 0 0 1 2 2z"></path> <path d="M9 10h.01"></path> <path d="M15 10h.01"></path> <path d="M9.5 13.5a3.5 3.5 0 0 0 5 0"></path> </svg> </div> <h3 class="use-case-title">Multilingual Sentiment Analysis</h3> <p class="use-case-desc">Analyze customer feedback in 23 languages. Detect emotions, themes, and sentiment across global markets.</p> <div class="use-case-features"> <p class="use-case-feature">Works with CSV/JSON, S3, BigQuery streams</p> <p class="use-case-feature">Labels: sentiment, emotion, topic, urgency</p> <p class="use-case-feature">Deploy in your VPC or on-prem</p> </div> <a href="https://huggingface.co/tabularisai/multilingual-sentiment-analysis" target="_blank" rel="noopener noreferrer" class="use-case-link">View on HuggingFace â</a> </div> <div class="use-case-item" data-industry="pii"> <div class="use-case-icon"> <svg width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.5"> <rect x="3" y="11" width="18" height="11" rx="2" ry="2"></rect> <path d="M7 11V7a5 5 0 0 1 10 0v4"></path> </svg> </div> <h3 class="use-case-title">PII Detection & Redaction</h3> <p class="use-case-desc">Identify and redact 42 types of personal data in EU languages. Keep sensitive information out of analytics and training pipelines.</p> <div class="use-case-features"> <p class="use-case-feature">Finds names, addresses, IBANs, IDs, emails, phones</p> <p class="use-case-feature">Redact, hash, or replace with tokens</p> <p class="use-case-feature">GDPR-first; batch or real-time via API</p> </div> <a href="https://huggingface.co/tabularisai/eu-pii-safeguard" target="_blank" rel="noopener noreferrer" class="use-case-link">View on HuggingFace â</a> </div> <div class="use-case-item" data-industry="medical"> <div class="use-case-icon"> <svg width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.5"> <path d="M22 12h-4l-3 9L9 3l-3 9H2"></path> </svg> </div> <h3 class="use-case-title">
307Medical Documents (DE)</h3> <p class="use-case-desc">Extract structure and insights from German Arztbriefe and clinical notes without PHI leaving your system.</p> <div class="use-case-features"> <p class="use-case-feature">Summarization tuned for medical text</p> <p class="use-case-feature">On-prem deployment for data sovereignty</p> <p class="use-case-feature">Audit logs + simple review UI</p> </div> <a href="/cdn-cgi/l/email-protection#e28b8c848da2968380978e83908b91cc838b" class="use-case-link">Contact us â</a> </div> <div class="use-case-item" data-industry="synthetic"> <div class="use-case-icon"> <svg width="48" height="48" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="1.5"> <rect x="2" y="7" width="20" height="14" rx="2" ry="2"></rect> <path d="M16 21V5a2 2 0 0 0-2-2h-4a2 2 0 0 0-2 2v16"></path> </svg> </div> <h3 class="use-case-title">Synthetic Data + Knowledge Distillation</h3> <p class="use-case-desc">Transfer intelligence from large models to efficient task-specific ones. Generate hyper-realistic synthetic data across text, images, and tables while protecting sensitive information.</p> <div class="use-case-features"> <p class="use-case-feature">Distill frontier teacher models into compact domain experts</p> <p class="use-case-feature">Privacy-first: train without real data exposure</p> <p class="use-case-feature">Production-ready: fast, cost-effective inference</p> </div> <a href="/cdn-cgi/l/email-protection#20494e464f60544142554c415249530e4149" class="use-case-link">Contact us â</a> </div> </div> </div> </section> <section class="text-animation-section"> <div class="text-content"> <div class="stats-section"> <div class="stat-item"> <div class="stat-category">Monthly Downloads</div> <div class="stat-number" data-target="500">0</div> <div class="stat-label">k+</div> </div> <div class="stat-item"> <div class="stat-category">Cost Reduction</div> <div class="stat-number" data-target="90">0</div> <div class="stat-label">%</div> </div> <div class="stat-item"> <div class="stat-category">Model Efficiency</div> <div class="stat-number" data-target="10">0</div> <div class="stat-label">x smaller</div> </div> </div> <div class="benchmark-note"> <p class="benchmark-text">500k+ monthly downloads. Our open-source models power teams worldwide.</p> </div> <div class="credibility-section"> <div class="credibility-card"> <h3 class="credibility-title">Built on Research. Ready for Production.</h3> <p class="credibility-text">Our models are grounded in peer-reviewed research from the University of Tübingen, published at top venues like ICLR and ICML. We don't just deploy AI - we invented the methods behind it.</p> <div class="credibility-stats"> <div class="cred-item"> <span class="cred-highlight">ICLR & ICML</span> <span class="cred-label">Published Research</span> </div> <div class="cred-item"> <span class="cred-highlight">Uni Tübingen & TUM</span> <span class="cred-label">Academic Roots</span> </div> <div class="cred-item"> <span class="cred-highlight">Open Source</span> <span class="cred-label">500k+ Monthly Downloads</span> </div> </div> <div class="credibility-links"> <a href="/research" class="cred-link">View Our Research â</a> <a href="/team" class="cred-link">Meet the Team â</a> </div> </div> </div> <!-- How to Start Section --> <div class="how-it-works-section"> <h3 class="how-it-works-title">How to Start</h3> <p class="how-it-works-subtitle">Enterprise AI deployment in three steps</p> <div class="steps-grid"> <div class="step-item"> <div class="step-number">1</div> <h4 class="step-title">Assess</h4> <p class="step-desc">We analyze your requirements and design specialized models for your use case.</p> </div> <div class="step-item"> <div class="step-number">2</div> <h4 class="step-title">Deploy</h4> <p class="step-desc">Models deploy in your environment on-premise, VPC, or edge with seamless integration.</p> </div> <div class="step-item"> <div class="step-number">3</div> <h4 class="step-title">Monitor</h4> <p class="step-desc">Continuous optimization and support as your AI scales with your business.</p> </div> </div> </div> <div class="faq-section"> <h3 class="faq-title">Frequently Asked Questions</h3> <div class="faq-grid"> <details class="faq-item"> <summary class="faq-question">What types of synthetic data can you generate?</summary> <p class="faq-answer">We generate realistic synthetic data across tabular (CSV, Parquet), text (NLP training data, documents), time-series, and images. All generated data preserves statistical properties while containing zero real PII.</p> </details> <details class="faq-item"> <summary class="faq-question">How does custom model training work?</summary> <p class="faq-answer">We analyze your use case, design a model architecture, train on your data (or synthetic data), and deliver optimized models. From simple classifiers to complex language models - any complexity, delivered production-ready.</p> </details> <details class="faq-item"> <summary class="faq-question">Is on-premise AI really cheaper than cloud APIs?</summary> <p class="faq-answer">Yes. Enterprise cloud AI API spending averages $50,000â$100,000/month for mid-scale deployments. On-premise deployment with optimized models typically achieves 70â90% cost savings with predictable fixed costs.</p> </details> <details class="faq-item"> <summary class="faq-question">Which compliance standards do you support?</summary> <p class="faq-answer">
307Our solutions support GDPR, HIPAA, SOC 2, PCI-DSS, and EU AI Act compliance. On-premise deployment keeps all data within your controlled environment, satisfying data residency requirements.</p> </details> </div> </div> <div class="cta-section"> <h3 class="cta-title">Ready to Get Started?</h3> <p class="cta-subtitle">From synthetic data to production models - let's build your AI together.</p> <button class="cta-button" onclick="window.location.href='mailto:[email protected]'" aria-label="Contact us">Contact us</button> </div> </div> </section> <div style="margin-top: 8rem;"></div> <footer class="site-footer"> <div class="footer-inner"> <div class="footer-grid"> <div class="footer-brand"> <a href="/" class="brand-mark">tabularis.ai</a> <p class="brand-tagline">Private, efficient, sovereign AI.</p> <div class="social" aria-label="Social links"> <a href="https://huggingface.co/tabularisai" target="_blank" rel="noopener noreferrer" aria-label="Hugging Face"> <svg fill="currentColor" fill-rule="evenodd" height="20" width="20" viewBox="0 0 24 24" 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