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.k{color:rgba(255,255,255,.8);}\n.psvr-scope .flow .node .t{font-size:13.5px;font-weight:700;color:var(--invert);}\n.psvr-scope .flow .node .sub{display:block;font-size:11.5px;font-weight:500;color:var(--invert-soft);margin-top:4px;}\n.psvr-scope .flow .node.hl .sub{color:rgba(255,255,255,.75);}\n.psvr-scope .flow .arrow{text-align:center;color:var(--invert-soft);font-size:20px;}\n@media (max-width:820px){.psvr-scope .flow .arrow{transform:rotate(90deg);}}\n.psvr-scope section:not(.deep) .flow .node{background:var(--bg-alt);border-color:var(--line);}\n.psvr-scope section:not(.deep) .flow .node .t{color:var(--ink);}\n.psvr-scope section:not(.deep) .flow .node .sub{color:var(--ink-soft);}\n.psvr-scope section:not(.deep) .flow .node .k{color:var(--brand-deep);}\n.psvr-scope section:not(.deep) .flow .arrow{color:var(--ink-faint);}\n.psvr-scope section:not(.deep) .flow .node.hl{background:linear-gradient(160deg,var(--brand-deep),var(--brand));border-color:var(--brand);}\n.psvr-scope section:not(.deep) .flow .node.hl .t,\n.psvr-scope section:not(.deep) .flow .node.hl .k,\n.psvr-scope section:not(.deep) .flow .node.hl .sub{color:#fff;}\n\n.psvr-scope .grid3.compliance .case{background:var(--bg-deep-alt);border-color:var(--line-deep);}\n.psvr-scope .grid3.compliance .case h3{color:var(--invert);}\n.psvr-scope .grid3.compliance .case p{color:var(--invert-soft);}\n.psvr-scope .grid3.compliance .icon{background:rgba(73,135,245,.18);color:#7dabf9;}\n\n.psvr-scope .tablewrap{overflow-x:auto;border:1px solid var(--line);border-radius:var(--radius);}\n.psvr-scope table.cmp{width:100%;border-collapse:collapse;min-width:680px;background:var(--bg);}\n.psvr-scope table.cmp th, .psvr-scope table.cmp td{padding:18px 20px;text-align:left;border-bottom:1px solid var(--line);vertical-align:top;}\n.psvr-scope table.cmp thead th{font-size:13.5px;font-family:\"JetBrains Mono\",monospace;font-weight:600;color:var(--ink-soft);background:var(--bg-alt);}\n.psvr-scope table.cmp thead th.hl{color:var(--brand);}\n.psvr-scope table.cmp td.feat{max-width:280px;}\n.psvr-scope table.cmp td.feat b{display:block;font-size:14.5px;font-weight:700;color:var(--ink);}\n.psvr-scope table.cmp td{font-size:14px;color:var(--ink-soft);}\n.psvr-scope table.cmp tbody tr:last-child td{border-bottom:none;}\n.psvr-scope .mark{display:inline-flex;align-items:center;gap:6px;font-weight:700;font-size:13.5px;}\n.psvr-scope .mark.yes{color:var(--good);}\n.psvr-scope .mark.no{color:var(--ink-faint);}\n.psvr-scope .mark.plain{color:var(--ink-soft);font-weight:600;}\n.psvr-scope .riskchip-note{display:block;font-size:11.5px;color:var(--ink-faint);margin-top:4px;font-family:\"Barlow\",sans-serif;}\n\n\/* dokumentli-specific additions *\/\n.psvr-scope .tag-soon{display:inline-flex;align-items:center;font-family:\"JetBrains Mono\",monospace;font-size:10px;font-weight:700;letter-spacing:.04em;text-transform:uppercase;color:var(--good);background:rgba(31,157,111,.14);border:1px solid rgba(31,157,111,.3);padding:3px 9px;border-radius:100px;white-space:nowrap;}\n.psvr-scope .deep .tag-soon,.psvr-scope .tag-soon.on-deep{color:#5bd6a0;background:rgba(31,157,111,.16);border-color:rgba(31,157,111,.35);}\n\n.psvr-scope .grid4{display:grid;grid-template-columns:repeat(4,1fr);gap:22px;}\n@media (max-width:1000px){.psvr-scope .grid4{grid-template-columns:1fr 1fr;}}\n@media (max-width:560px){.psvr-scope .grid4{grid-template-columns:1fr;}}\n\n.psvr-scope .barchart-card{background:var(--bg-deep-alt);border:1px solid var(--line-deep);border-radius:var(--radius);padding:28px 26px 20px;}\n.psvr-scope .barchart-card + .barchart-card{margin-top:22px;}\n.psvr-scope .barchart-card .bc-head{display:flex;align-items:flex-start;justify-content:space-between;gap:14px;margin-bottom:24px;flex-wrap:wrap;}\n.psvr-scope .barchart-card .bc-head h3{font-size:15.5px;color:var(--invert);font-weight:700;max-width:56ch;}\n.psvr-scope .barchart-card .bc-flag{font-family:\"JetBrains 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.bar.best::before{content:\"\";position:absolute;top:-38px;left:-8px;right:-8px;bottom:0;background:linear-gradient(180deg,rgba(46,196,182,.14),rgba(46,196,182,0) 75%);border-radius:10px 10px 0 0;z-index:0;}\n.psvr-scope .barchart .bar.best .crown,.psvr-scope .barchart .bar.best .val,.psvr-scope .barchart .bar.best .fill,.psvr-scope .barchart .bar.best .lbl{position:relative;z-index:1;}\n.psvr-scope .barchart .bar.best .crown{display:block;font-family:\"JetBrains Mono\",monospace;font-size:9.5px;font-weight:700;letter-spacing:.04em;text-transform:uppercase;color:var(--teal);margin-bottom:5px;white-space:nowrap;}\n.psvr-scope .barchart .bar.best .fill{background:linear-gradient(180deg,var(--teal),var(--brand));box-shadow:0 12px 26px -8px rgba(46,196,182,.5);}\n.psvr-scope .barchart .bar.best .val{color:var(--invert);font-weight:700;font-size:13.5px;}\n.psvr-scope .barchart .bar .lbl{margin-top:10px;font-size:11px;color:var(--invert-soft);text-align:center;line-height:1.25;}\n.psvr-scope .barchart .bar.best .lbl{color:var(--invert);font-weight:700;}\n@media (max-width:640px){.psvr-scope .barchart{height:190px;}.psvr-scope .barchart .lbl{font-size:9.5px;}}\n\n.psvr-scope .decision-grid{display:grid;grid-template-columns:1fr 1fr;gap:22px;}\n@media (max-width:720px){.psvr-scope .decision-grid{grid-template-columns:1fr;}}\n.psvr-scope .decision{border:1px solid var(--line);border-radius:var(--radius);padding:26px 26px 24px;background:var(--bg);}\n.psvr-scope .decision.yes{border-color:rgba(31,157,111,.35);background:rgba(31,157,111,.05);}\n.psvr-scope .decision .dh{display:flex;align-items:center;gap:12px;margin-bottom:16px;}\n.psvr-scope .decision .dh .icon{width:36px;height:36px;border-radius:9px;display:flex;align-items:center;justify-content:center;flex:0 0 auto;}\n.psvr-scope .decision.yes .dh .icon{background:rgba(31,157,111,.14);color:var(--good);}\n.psvr-scope .decision.no .dh .icon{background:var(--bg-alt);color:var(--ink-soft);}\n.psvr-scope .decision .dh .icon svg{width:19px;height:19px;}\n.psvr-scope .decision .dh h3{font-size:16.5px;}\n.psvr-scope .decision ul{margin:14px 0 0;padding-left:20px;display:flex;flex-direction:column;gap:9px;}\n.psvr-scope .decision li{font-size:14.5px;color:var(--ink-soft);}\n.psvr-scope .decision.plain{border-color:var(--line);}\n.psvr-scope .decision .kicker{display:block;font-family:\"JetBrains Mono\",monospace;font-size:11px;font-weight:700;letter-spacing:.05em;text-transform:uppercase;color:var(--brand);margin-bottom:8px;}\n.psvr-scope .decision ul.plain{padding-left:0;list-style:none !important;}\n.psvr-scope .decision ul.plain li{padding-left:18px;position:relative;}\n.psvr-scope .decision ul.plain li::before{content:\"\";position:absolute;left:0;top:7px;width:5px;height:5px;border-radius:50%;background:var(--brand);}\n.psvr-scope .decision ul.plain li b{color:var(--ink);font-weight:600;}\n\n.psvr-scope .note{display:flex;gap:16px;align-items:flex-start;border-radius:var(--radius);padding:24px 26px;}\n.psvr-scope .note.brand{background:linear-gradient(120deg,var(--brand-deep),var(--brand) 140%);color:#fff;}\n.psvr-scope .note.brand h3{color:#fff;}\n.psvr-scope .note.brand p{color:rgba(255,255,255,.9);}\n.psvr-scope .note.plain{background:var(--bg-alt);border:1px solid var(--line);}\n.psvr-scope .note.deepbox{background:var(--bg-deep-alt);border:1px solid var(--line-deep);}\n.psvr-scope .note.deepbox h3{color:var(--invert);}\n.psvr-scope .note.deepbox p{color:var(--invert-soft);}\n.psvr-scope .note .icon{width:38px;height:38px;border-radius:10px;background:rgba(255,255,255,.18);display:flex;align-items:center;justify-content:center;flex:0 0 auto;color:#fff;}\n.psvr-scope .note.plain .icon{background:var(--brand-glow);color:var(--brand);}\n.psvr-scope .note.deepbox .icon{background:rgba(73,135,245,.18);color:#7dabf9;}\n.psvr-scope .note .icon svg{width:20px;height:20px;}\n.psvr-scope .note h3{font-size:16px;margin-bottom:6px;}\n.psvr-scope .note p{font-size:14.5px;line-height:1.55;}\n.psvr-scope .note .kicker{display:block;font-family:\"JetBrains Mono\",monospace;font-size:11px;font-weight:700;letter-spacing:.05em;text-transform:uppercase;margin-bottom:5px;opacity:.85;}\n\n.psvr-scope .miniflow{display:flex;align-items:center;gap:7px;margin-bottom:20px;flex-wrap:wrap;}\n.psvr-scope .miniflow .mf-node{width:34px;height:34px;border-radius:8px;background:var(--brand-glow);color:var(--brand);display:flex;align-items:center;justify-content:center;flex:0 0 auto;}\n.psvr-scope .miniflow .mf-node svg{width:16px;height:16px;}\n.psvr-scope .miniflow .mf-arrow{color:var(--ink-faint);font-size:14px;}\n\n.psvr-scope .deploy-card{background:var(--bg-deep-alt);border:1px solid var(--line-deep);border-radius:var(--radius);padding:26px 24px;display:flex;flex-direction:column;}\n.psvr-scope .deploy-card.hl{border-color:var(--brand);box-shadow:0 0 0 1px var(--brand);}\n.psvr-scope .deploy-card .icon{width:40px;height:40px;border-radius:10px;background:rgba(73,135,245,.18);color:#7dabf9;display:flex;align-items:center;justify-content:center;margin-bottom:14px;}\n.psvr-scope .deploy-card .icon svg{width:21px;height:21px;}\n.psvr-scope .deploy-card h3{font-size:16.5px;margin-bottom:12px;color:var(--invert);}\n.psvr-scope .deploy-card .dtag{display:inline-block;font-family:\"JetBrains Mono\",monospace;font-size:10px;font-weight:700;letter-spacing:.05em;text-transform:uppercase;color:#9db8f7;background:rgba(73,135,245,.16);padding:4px 10px;border-radius:100px;margin-bottom:14px;align-self:flex-start;}\n.psvr-scope .deploy-card ul{margin:0;padding:0;list-style:none !important;display:flex;flex-direction:column;gap:10px;}\n.psvr-scope .deploy-card li{font-size:13.5px;color:var(--invert-soft);padding-left:16px;position:relative;}\n.psvr-scope .deploy-card li::before{content:\"\";position:absolute;left:0;top:7px;width:5px;height:5px;border-radius:50%;background:#7dabf9;}\n.psvr-scope .deploy-card li b{color:var(--invert);font-weight:600;}\n\n.psvr-scope .genspec{display:grid;grid-template-columns:1fr 1fr;gap:20px;margin-top:26px;}\n@media (max-width:640px){.psvr-scope .genspec{grid-template-columns:1fr;}}\n.psvr-scope .genspec > div{border:1px solid var(--line);border-radius:var(--radius);padding:22px 24px;}\n.psvr-scope .genspec > div.spec{border-color:rgba(73,135,245,.35);background:var(--brand-glow);}\n.psvr-scope .genspec h4{font-size:15px;margin-bottom:8px;}\n.psvr-scope .genspec p{font-size:14px;color:var(--ink-soft);}\n\n.psvr-scope .costcard{background:var(--bg);border:1px solid var(--line);border-radius:var(--radius);padding:28px 26px 20px;box-shadow:var(--shadow);}\n.psvr-scope .costcard .cc-head h3{font-size:15.5px;margin-bottom:6px;}\n.psvr-scope .costcard .cc-head p{font-size:13px;color:var(--ink-faint);max-width:64ch;margin-bottom:18px;}\n.psvr-scope .costlegend{display:flex;gap:22px;margin-bottom:18px;font-size:12.5px;color:var(--ink-soft);flex-wrap:wrap;}\n.psvr-scope .costlegend span{display:flex;align-items:center;gap:7px;}\n.psvr-scope .costlegend i{width:11px;height:11px;border-radius:3px;display:inline-block;}\n.psvr-scope .costlegend i.ppc{background:#cdd4e2;}\n.psvr-scope .costlegend i.sub{background:linear-gradient(180deg,var(--teal),var(--brand));}\n.psvr-scope .costchart{display:flex;align-items:flex-end;gap:8px;height:150px;border-bottom:1px solid var(--line);padding-bottom:2px;}\n.psvr-scope .costchart .cgroup{flex:1;display:flex;align-items:flex-end;gap:4px;height:100%;}\n.psvr-scope .costchart .cbar{flex:1;border-radius:4px 4px 0 0;}\n.psvr-scope .costchart .cbar.ppc{background:#cdd4e2;}\n.psvr-scope .costchart .cbar.sub{background:linear-gradient(180deg,var(--teal),var(--brand));}\n.psvr-scope .costaxis{display:flex;gap:8px;margin-top:10px;}\n.psvr-scope .costaxis span{flex:1;text-align:center;font-family:\"JetBrains Mono\",monospace;font-size:10.5px;color:var(--ink-faint);}\n.psvr-scope .cost-flag{margin-left:auto;font-family:\"JetBrains Mono\",monospace;font-size:10.5px;font-weight:700;letter-spacing:.04em;text-transform:uppercase;color:var(--ink-faint);}\n\n.psvr-scope .faq{max-width:760px;}\n.psvr-scope .faqitem{border-bottom:1px solid var(--line);}\n.psvr-scope .faqitem:first-child{border-top:1px solid var(--line);}\n.psvr-scope .faqitem button.q{width:100%;display:flex;align-items:center;justify-content:space-between;gap:16px;background:none;border:none;text-align:left;padding:20px 4px;cursor:pointer;font-family:\"Barlow\",sans-serif;font-size:16px;font-weight:700;color:var(--ink);}\n.psvr-scope .faqitem .q .plus{font-family:\"JetBrains Mono\",monospace;color:var(--brand);font-size:18px;flex:0 0 auto;transition:transform .18s ease;}\n.psvr-scope .faqitem.open .q .plus{transform:rotate(45deg);}\n.psvr-scope .faqitem .a{max-height:0;overflow:hidden;transition:max-height .22s ease;}\n.psvr-scope .faqitem.open .a{max-height:320px;}\n.psvr-scope .faqitem .a p{padding:0 4px 20px;font-size:15.5px;color:var(--ink-soft);max-width:68ch;}\n\n.psvr-scope .finalcta{background:linear-gradient(120deg,var(--brand-deep),var(--brand) 60%, var(--teal) 130%);border-radius:20px;padding:56px 48px;text-align:center;color:#fff;}\n@media (max-width:720px){.psvr-scope .finalcta{padding:40px 24px;}}\n.psvr-scope .finalcta h2{color:#fff;font-size:clamp(24px,3vw,32px);margin-bottom:14px;}\n.psvr-scope .finalcta p{color:rgba(255,255,255,.85);max-width:52ch;margin:0 auto 28px;font-size:16px;}\n.psvr-scope .finalcta .ctas{display:flex;gap:14px;justify-content:center;flex-wrap:wrap;}\n.psvr-scope .finalcta .btn{background:#fff;color:var(--brand-deep);border-color:#fff;box-shadow:0 10px 24px -10px rgba(0,0,0,.35);}\n.psvr-scope .finalcta .btn:hover{background:#f2f6ff;color:var(--brand-deep);}\n.psvr-scope .finalcta .btn.ghost{background:transparent;color:#fff;border-color:rgba(255,255,255,.4);box-shadow:none;}\n.psvr-scope .finalcta .btn.ghost:hover{background:rgba(255,255,255,.12);color:#fff;}\n.psvr-scope .finalcta .cite{background:rgba(255,255,255,.14);border-color:rgba(255,255,255,.25);color:#fff;margin-top:22px;}\n.psvr-scope .finalcta .cite b{color:#fff;}\n\n.psvr-scope .linkcards{display:grid;grid-template-columns:repeat(3,1fr);gap:20px;margin-top:40px;}\n@media (max-width:820px){.psvr-scope .linkcards{grid-template-columns:1fr;}}\n.psvr-scope .linkcard{display:flex;gap:16px;align-items:flex-start;background:var(--bg);border:1px solid var(--line);border-radius:var(--radius);padding:22px;box-shadow:var(--shadow);transition:border-color .15s ease, transform .15s ease;}\n.psvr-scope a.linkcard:hover{border-color:var(--brand);transform:translateY(-2px);}\n.psvr-scope .linkcard .icon{width:36px;height:36px;border-radius:9px;background:var(--brand-glow);color:var(--brand);display:flex;align-items:center;justify-content:center;flex:0 0 auto;}\n.psvr-scope .linkcard .icon svg{width:19px;height:19px;}\n.psvr-scope .linkcard h4{font-size:15px;margin-bottom:5px;}\n.psvr-scope .linkcard p{font-size:13.5px;color:var(--ink-soft);}\n.psvr-scope .linkcard .go{color:var(--brand);font-weight:700;font-size:13px;margin-top:6px;display:inline-block;}\n\n.psvr-scope .compliance-badges{margin-top:40px;padding-top:32px;border-top:1px solid var(--line-deep);}\n.psvr-scope .compliance-badges .badges-label{display:block;font-family:\"JetBrains Mono\",monospace;font-size:11.5px;font-weight:600;letter-spacing:.06em;text-transform:uppercase;color:var(--invert-soft);margin-bottom:16px;}\n.psvr-scope .compliance-badges .badges-row{display:flex;gap:16px;flex-wrap:wrap;align-items:center;}\n.psvr-scope .compliance-badges .badge-logo{width:64px;height:64px;background:#fff;border-radius:12px;padding:8px;display:flex;align-items:center;justify-content:center;box-shadow:0 6px 16px -8px rgba(0,0,0,.35);flex:0 0 auto;}\n.psvr-scope .compliance-badges .badge-logo img{width:100%;height:100%;object-fit:contain;}\n\n.psvr-scope::selection{background:var(--brand-glow);color:var(--brand-deep);}\n@media (prefers-reduced-motion: reduce){.psvr-scope *{transition:none !important;}}\n<\/style>\n\n<div class=\"psvr-scope\">\n\n<section class=\"hero\">\n  <div class=\"wrap\">\n    <div class=\"hero-grid\">\n      <div>\n        <span class=\"eyebrow\">Dokumentli\u00ae \u00b7 Sovereign Document AI<\/span>\n        <h1>Dokumentli\u00ae \u2013 The AI model that beats LLMs at documents.<\/h1>\n        <p class=\"lede\">Dokumentli\u00ae reads, classifies, and structures business documents more precisely and faster than general-purpose frontier models \u2013 and can run fully air-gapped on a single consumer GPU with 24 GB VRAM.<\/p>\n        <div class=\"ctas\">\n          <a class=\"btn\" href=\"https:\/\/playground.parashift.io\/\" target=\"_blank\" rel=\"noopener\">Try the model live<\/a>\n          <a class=\"btn ghost\" href=\"#benchmarks\">View benchmark results \u2193<\/a>\n        <\/div>\n        <div class=\"microproof\">\n          <span><i class=\"dot\"><\/i> Faster<\/span>\n          <span><i class=\"dot\"><\/i> More accurate<\/span>\n          <span><i class=\"dot\"><\/i> More cost-effective<\/span>\n          <span><i class=\"dot\"><\/i> Runs on 1 GPU (24 GB)<\/span>\n        <\/div>\n      <\/div>\n      <div class=\"ai-aura\">\n        <span class=\"aura-vignette\"><\/span>\n        <span class=\"aura-stars s2\"><\/span>\n        <span class=\"aura-stars\"><\/span>\n        <span class=\"aura-nebula2\"><\/span>\n        <span class=\"aura-glow\"><\/span>\n        <span class=\"aura-grid\"><\/span>\n        <span class=\"aura-radar\"><\/span>\n        <span 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<\/div>\n<\/section>\n\n<section>\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">At a Glance<\/span>\n      <h2>Runs on 1 GPU with 24 GB. Beats seven models at documents.<\/h2>\n      <p>Built for European enterprises and regulated industries with high, recurring document volumes \u2013 from financial services and insurance to construction, trade, and logistics.<\/p>\n    <\/div>\n    <div class=\"kpiband four\">\n      <div class=\"kpi\"><div class=\"num sm\">88%<\/div><p>Avg. accuracy (cANLS@0.8), highest score among 7 models tested<\/p><\/div>\n      <div class=\"kpi\"><div class=\"num sm\">2.0\u00d7<\/div><p>faster on average than the most accurate of the six reference models<\/p><\/div>\n      <div class=\"kpi\"><div class=\"num sm\">4<\/div><p>Deployment options, from on-prem to API<\/p><\/div>\n      <div class=\"kpi\"><div class=\"num sm\">24 GB<\/div><p>of GPU memory are enough for full air-gapped operation on a single consumer graphics card<\/p><\/div>\n    <\/div>\n    <div class=\"note plain\" style=\"margin-top:40px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"5\" y=\"10.5\" width=\"14\" height=\"10\" rx=\"1.5\"\/><path d=\"M8 10.5V7a4 4 0 1 1 8 0v3.5\"\/><\/svg><\/div>\n      <div><h3 style=\"color:var(--ink)\">Air-gapped capable<\/h3><p style=\"color:var(--ink-soft)\">Fully on-prem operation on a single consumer GPU with 24 GB VRAM \u2013 no data center, no cloud connection required.<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"alt\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Fundamentals<\/span>\n      <h2>What Is a Small Special-Purpose Vision Language Model?<\/h2>\n      <p>A <b>Vision Language Model (VLM)<\/b> processes image and text together. It reads a document page directly as an image \u2013 including layout, tables, stamps, and handwriting \u2013 and answers a text-based query about it. No separate OCR pre-processing step is required.<\/p>\n    <\/div>\n    <div class=\"flow\">\n      <div class=\"node\"><div class=\"k\">Input<\/div><div class=\"t\">Document (image)<\/div><span class=\"sub\">Layout, tables, stamps<\/span><\/div>\n      <div class=\"arrow\">\u2192<\/div>\n      <div class=\"node hl\"><div class=\"k\">Core Model<\/div><div class=\"t\">Dokumentli\u00ae VLM<\/div><span class=\"sub\">Image + text in one step<\/span><\/div>\n      <div class=\"arrow\">\u2192<\/div>\n      <div class=\"node\"><div class=\"k\">Output<\/div><div class=\"t\">Structured data<\/div><span class=\"sub\">JSON in your own schema<\/span><\/div>\n    <\/div>\n    <div class=\"grid3\" style=\"margin-top:44px;\">\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 3h7l4 4v13a1 1 0 0 1-1 1H7a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1Z\"\/><path d=\"M14 3v4h4\"\/><path d=\"M9 12h6\"\/><path d=\"M9 15.5h6\"\/><\/svg><\/div>\n        <h3>Image + text in one model<\/h3>\n        <p>Layout, tables, and text content are interpreted together, without a separate OCR pipeline.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l9 5-9 5-9-5 9-5Z\"\/><path d=\"M3 13l9 5 9-5\"\/><\/svg><\/div>\n        <h3>Specialized for documents<\/h3>\n        <p>Trained on real business documents instead of general web text.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"6\" y=\"6\" width=\"12\" height=\"12\" rx=\"2\"\/><path d=\"M9 3v3M15 3v3M9 18v3M15 18v3M3 9h3M3 15h3M18 9h3M18 15h3\"\/><\/svg><\/div>\n        <h3>Compact<\/h3>\n        <p>Fewer parameters and lower compute per document \u2013 runs entirely on a single consumer GPU with 24 GB VRAM.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"kpiband\" style=\"grid-template-columns:1fr 1fr;max-width:680px;margin-top:40px;gap:22px;\">\n      <div class=\"kpi\"><div class=\"num sm\">1 GPU<\/div><p>is enough for full air-gapped operation \u2013 no data center, no cloud connection needed.<\/p><\/div>\n      <div class=\"kpi\"><div class=\"num sm\">24 GB<\/div><p>of VRAM on a single consumer graphics card are enough to run the entire model.<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"deep\" id=\"benchmarks\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\" style=\"background:rgba(73,135,245,.18);color:#7dabf9;border-color:rgba(73,135,245,.3)\">Benchmark Results<\/span>\n      <h2>Highest Accuracy at the Highest Speed<\/h2>\n      <p>In an independent test across 5 benchmark datasets comprising a total of 3,368 real business documents, Dokumentli\u00ae was tested against six current reference models: Claude Opus 4.8, GPT-5.6 Sol, Gemini 3.6 Flash, Gemini 3.7 Flash, Qwen3.6-Plus, and the open model Gemma 4 26B-A4B-IT. The quality metric is cANLS@0.8 (Average Normalized Levenshtein Similarity with a threshold of 0.8), a common variant of the ANLS industry standard for evaluating document extraction.<\/p>\n    <\/div>\n\n    <div class=\"barchart-card\">\n      <div class=\"bc-head\">\n        <h3>Avg. accuracy (cANLS@0.8) per model, averaged across 5 benchmarks<\/h3>\n        <span class=\"bc-flag\">More Accuracy \u2191<\/span>\n      <\/div>\n      <div class=\"barchart\">\n        <div class=\"bar best\"><span class=\"crown\">Best score<\/span><span class=\"val\">88.4%<\/span><div class=\"fill\" style=\"height:135px\"><\/div><span class=\"lbl\">Dokumentli\u00ae<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">83.5%<\/span><div class=\"fill\" style=\"height:112px\"><\/div><span class=\"lbl\">Gemini 3.6<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">82.9%<\/span><div class=\"fill\" style=\"height:109px\"><\/div><span class=\"lbl\">Gemini 3.7<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">81.8%<\/span><div class=\"fill\" style=\"height:104px\"><\/div><span class=\"lbl\">GPT-5.6 Sol<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">82.1%<\/span><div class=\"fill\" style=\"height:105px\"><\/div><span class=\"lbl\">Qwen3.6<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">81.0%<\/span><div class=\"fill\" style=\"height:100px\"><\/div><span class=\"lbl\">Claude 4.8<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">69.0%<\/span><div class=\"fill\" style=\"height:43px\"><\/div><span class=\"lbl\">Gemma 4 26B<\/span><\/div>\n      <\/div>\n      <p class=\"bc-axisnote\">Scale starts at 60% cANLS@0.8 for better readability of the differences; see bar labels for exact values.<\/p>\n    <\/div>\n\n    <div class=\"barchart-card\">\n      <div class=\"bc-head\">\n        <h3>Avg. processing speed per model, documents per second<\/h3>\n        <span class=\"bc-flag\">More Speed \u2191<\/span>\n      <\/div>\n      <div class=\"barchart\">\n        <div class=\"bar best\"><span class=\"crown\">Best score<\/span><span class=\"val\">0.86<\/span><div class=\"fill\" style=\"height:130px\"><\/div><span class=\"lbl\">Dokumentli\u00ae<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.82<\/span><div class=\"fill\" style=\"height:124px\"><\/div><span class=\"lbl\">Gemini 3.7<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.80<\/span><div class=\"fill\" style=\"height:121px\"><\/div><span class=\"lbl\">Claude 4.8<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.43<\/span><div class=\"fill\" style=\"height:65px\"><\/div><span class=\"lbl\">Gemini 3.6<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.34<\/span><div class=\"fill\" style=\"height:51px\"><\/div><span class=\"lbl\">Gemma 4 26B<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.32<\/span><div class=\"fill\" style=\"height:48px\"><\/div><span class=\"lbl\">GPT-5.6 Sol<\/span><\/div>\n        <div class=\"bar\"><span class=\"val\">0.04<\/span><div class=\"fill\" style=\"height:6px\"><\/div><span class=\"lbl\">Qwen3.6<\/span><\/div>\n      <\/div>\n    <\/div>\n\n    <div class=\"grid3 compliance\" style=\"grid-template-columns:1fr 1fr;margin-top:22px;\">\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M9 12.5l2 2 4-4.5\"\/><circle cx=\"12\" cy=\"12\" r=\"9\"\/><\/svg><\/div>\n        <h3>5 \/ 5<\/h3>\n        <p>Benchmarks in which Dokumentli\u00ae outperforms Gemini 3.6 Flash, the strongest of the six reference models.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"6\" cy=\"6\" r=\"2.2\"\/><circle cx=\"18\" cy=\"6\" r=\"2.2\"\/><circle cx=\"12\" cy=\"18\" r=\"2.2\"\/><path d=\"M7.8 7.2L11 16M16.2 7.2L13 16\"\/><\/svg><\/div>\n        <h3>7<\/h3>\n        <p>models tested in total: Dokumentli\u00ae plus six general-purpose frontier models as reference.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"note deepbox\" style=\"margin-top:22px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 3h7l4 4v13a1 1 0 0 1-1 1H7a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1Z\"\/><path d=\"M14 3v4h4\"\/><path d=\"M9 12h6\"\/><path d=\"M9 15.5h6\"\/><\/svg><\/div>\n      <div><h3>For details, see the Benchmark Report<\/h3><p>Results by industry and model, confidence intervals, positioning matrices, and the full methodology are documented in the separate <b style=\"color:var(--invert)\">Parashift Dokumentli\u00ae Benchmark Report<\/b> .<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section>\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Specialization<\/span>\n      <h2>Why a Specialized Model Beats General-Purpose LLMs<\/h2>\n      <p>General-purpose frontier models are trained to cover a very broad range of tasks. For the narrowly defined task of \"read this business document and extract these fields,\" that training objective misses the actual task. Four factors explain why a smaller, specialized model comes out ahead in these benchmarks:<\/p>\n    <\/div>\n    <div class=\"usecase-feature\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l9 5-9 5-9-5 9-5Z\"\/><path d=\"M3 13l9 5 9-5\"\/><\/svg><\/div>\n      <div>\n        <span class=\"kicker\">Training Data Focus<\/span>\n        <h3>Millions of real business documents instead of general web text<\/h3>\n        <p>Including the quirks of invoices, freight documents, and contracts from regulated industries.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"usecase-feature\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 3h7l4 4v13a1 1 0 0 1-1 1H7a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1Z\"\/><path d=\"M14 3v4h4\"\/><path d=\"M12 11v5\"\/><path d=\"M9.5 13.5h5\"\/><\/svg><\/div>\n      <div>\n        <span class=\"kicker\">Architecture for Layout Understanding<\/span>\n        <h3>Image and text are processed in a single step<\/h3>\n        <p>No lossy OCR pre-processing step \u2013 relevant for tables, multi-column layouts, stamps, and handwritten notes.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"usecase-feature\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"8.5\"\/><circle cx=\"12\" cy=\"12\" r=\"5\"\/><circle cx=\"12\" cy=\"12\" r=\"1.4\" fill=\"currentColor\" stroke=\"none\"\/><\/svg><\/div>\n      <div>\n        <span class=\"kicker\">Lower Context Requirement<\/span>\n        <h3>A smaller context budget per request<\/h3>\n        <p>This noticeably reduces latency and compute per document \u2013 and is what makes operation on a single consumer GPU with 24 GB VRAM possible in the first place.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"usecase-feature\" style=\"margin-bottom:0;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M4 6h9M17 6h3M4 12h3M11 12h9M4 18h13\"\/><circle cx=\"15\" cy=\"6\" r=\"2\"\/><circle cx=\"7\" cy=\"12\" r=\"2\"\/><circle cx=\"16\" cy=\"18\" r=\"2\"\/><\/svg><\/div>\n      <div>\n        <span class=\"kicker\">Fine-Tunable on Your Own Document Types <span class=\"tag-soon\">Coming soon<\/span><\/span>\n        <h3>Continuous fine-tuning instead of just prompt adjustments<\/h3>\n        <p>Fine-tuning on company-specific templates and edge cases, instead of just generic prompt adjustments.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"genspec\">\n      <div>\n        <h4>Generalist (general-purpose LLM)<\/h4>\n        <p>One model, many possible tasks: conversation, code, world knowledge, documents. Document understanding is one capability among many, not the training focus.<\/p>\n      <\/div>\n      <div class=\"spec\">\n        <h4>Specialist (Dokumentli\u00ae)<\/h4>\n        <p>One model, one task: reading, classifying, and structuring business documents. Training data, architecture, and context budget are fully aligned to it.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"alt\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Boundaries<\/span>\n      <h2>What Dokumentli\u00ae Can't Do<\/h2>\n      <p>The specialization that makes Dokumentli\u00ae strong at document intelligence tasks is also a deliberate boundary: Dokumentli\u00ae is not a general-purpose assistant. Outside document processing, a general-purpose model \u2014 or better yet, a model specialized for the specific automation task \u2014 is the right choice.<\/p>\n    <\/div>\n    <div class=\"tablewrap\">\n      <table class=\"cmp\">\n        <thead>\n          <tr>\n            <th style=\"min-width:260px\">Task<\/th>\n            <th class=\"hl\">Dokumentli\u00ae<\/th>\n            <th>General-purpose frontier model<\/th>\n          <\/tr>\n        <\/thead>\n        <tbody>\n          <tr>\n            <td class=\"feat\"><b>Classify Documents &amp; Extract Fields<\/b><\/td>\n            <td><span class=\"mark yes\">\u2713 Core task, trained for it<\/span><\/td>\n            <td><span class=\"mark no\">\u2715 Possible<\/span><span class=\"riskchip-note\">with lower accuracy and speed, higher costs, and greater security\/compliance overhead<\/span><\/td>\n          <\/tr>\n          <tr>\n            <td class=\"feat\"><b>Free-Form Reasoning &amp; Open Conversation<\/b><\/td>\n            <td><span class=\"mark no\">\u2715 Not intended<\/span><\/td>\n            <td><span class=\"mark plain\">\u2713 Core task<\/span><\/td>\n          <\/tr>\n          <tr>\n            <td class=\"feat\"><b>Programming \/ Code Generation<\/b><\/td>\n            <td><span class=\"mark no\">\u2715 Not intended<\/span><\/td>\n            <td><span class=\"mark plain\">\u2713 Core task<\/span><\/td>\n          <\/tr>\n          <tr>\n            <td class=\"feat\"><b>General knowledge questions outside document content<\/b><\/td>\n            <td><span class=\"mark no\">\u2715 Not intended<\/span><\/td>\n            <td><span class=\"mark plain\">\u2713 Core task<\/span><\/td>\n          <\/tr>\n          <tr>\n            <td class=\"feat\"><b>Free-Form Creative Writing<\/b><\/td>\n            <td><span class=\"mark no\">\u2715 Not intended<\/span><\/td>\n            <td><span class=\"mark plain\">\u2713 Core task<\/span><\/td>\n          <\/tr>\n          <tr>\n            <td class=\"feat\"><b>Multi-step agentic tasks unrelated to documents<\/b><\/td>\n            <td><span class=\"mark no\">\u2715 Not intended<\/span><\/td>\n            <td><span class=\"mark plain\">\u2713 Possible<\/span><\/td>\n          <\/tr>\n        <\/tbody>\n      <\/table>\n    <\/div>\n    <div class=\"decision-grid\" style=\"margin-top:28px;\">\n      <div class=\"decision yes\">\n        <div class=\"dh\">\n          <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"9\"\/><path d=\"M8 12.5l2.5 2.5L16 9.5\"\/><\/svg><\/div>\n          <h3>Use Dokumentli\u00ae When\u2026<\/h3>\n        <\/div>\n        <ul>\n          <li>high volumes of business documents need to be classified or have fields extracted from them<\/li>\n          <li>data sovereignty, air-gapped operation, or predictable costs matter<\/li>\n          <li>structured, schema-compliant output is needed instead of free text<\/li>\n        <\/ul>\n      <\/div>\n      <div class=\"decision no\">\n        <div class=\"dh\">\n          <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"6\" cy=\"6\" r=\"2.2\"\/><circle cx=\"18\" cy=\"6\" r=\"2.2\"\/><circle cx=\"12\" cy=\"18\" r=\"2.2\"\/><path d=\"M7.8 7.2L11 16M16.2 7.2L13 16\"\/><\/svg><\/div>\n          <h3>Use a General-Purpose LLM When\u2026<\/h3>\n        <\/div>\n        <ul>\n          <li>the task involves open-ended reasoning, conversation, or code<\/li>\n          <li>general world knowledge outside the document content is required<\/li>\n          <li>it involves free-form creative writing or agentic tasks unrelated to documents<\/li>\n        <\/ul>\n      <\/div>\n    <\/div>\n    <div class=\"note plain\" style=\"margin-top:22px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"6\" cy=\"6\" r=\"2.2\"\/><circle cx=\"18\" cy=\"6\" r=\"2.2\"\/><circle cx=\"12\" cy=\"18\" r=\"2.2\"\/><path d=\"M7.8 7.2L11 16M16.2 7.2L13 16\"\/><\/svg><\/div>\n      <div><h3 style=\"color:var(--ink)\">Combinable, Not Exclusive<\/h3><p style=\"color:var(--ink-soft)\">Companies use Dokumentli\u00ae specifically for inbound document processing and combine it, where needed, with general-purpose models for downstream steps unrelated to documents. Both can be orchestrated through your own workflow solution.<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"deep\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\" style=\"background:rgba(73,135,245,.18);color:#7dabf9;border-color:rgba(73,135,245,.3)\">Deployment Options<\/span>\n      <h2>Four Ways to Run Dokumentli\u00ae<\/h2>\n      <p>Depending on your data sovereignty, compliance, and integration requirements, Dokumentli\u00ae can be run in four ways \u2014 from fully isolated operation in your own data center to direct API integration.<\/p>\n    <\/div>\n    <div class=\"note deepbox\" style=\"margin-bottom:28px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l9 5-9 5-9-5 9-5Z\"\/><path d=\"M3 13l9 5 9-5\"\/><\/svg><\/div>\n      <div><h3>The Model and the Node Component<\/h3><p>Dokumentli\u00ae is the AI model itself. For easy deployment on your own hardware, Parashift additionally provides the <b style=\"color:var(--invert)\">Dokumentli\u00ae Node<\/b>, a lightweight component that packages the model and enables on-prem or air-gapped setup in a short time, without having to build your own deployment setup.<\/p><\/div>\n    <\/div>\n    <div class=\"grid4\">\n      <div class=\"deploy-card hl\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"4\" y=\"4\" width=\"16\" height=\"6\" rx=\"1.2\"\/><rect x=\"4\" y=\"14\" width=\"16\" height=\"6\" rx=\"1.2\"\/><circle cx=\"7.5\" cy=\"7\" r=\".9\" fill=\"currentColor\" stroke=\"none\"\/><circle cx=\"7.5\" cy=\"17\" r=\".9\" fill=\"currentColor\" stroke=\"none\"\/><\/svg><\/div>\n        <h3>On-Prem \/ Own Hardware<\/h3>\n        <span class=\"dtag\">Maximum Data Sovereignty<\/span>\n        <ul>\n          <li><b>Location:<\/b> your own data center, via Dokumentli\u00ae Node<\/li>\n          <li><b>Air-gapped capable:<\/b> no data leaves your own network<\/li>\n          <li><b>Hardware:<\/b> one consumer-grade GPU with 24 GB VRAM is enough<\/li>\n          <li><b>Typical for:<\/b> the highest compliance requirements, no internet connection needed<\/li>\n        <\/ul>\n      <\/div>\n      <div class=\"deploy-card\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 18a4.5 4.5 0 0 1-.5-8.97A5.5 5.5 0 0 1 17.2 8.2 4 4 0 0 1 16.5 18H7Z\"\/><\/svg><\/div>\n        <h3>Private Cloud Instance<\/h3>\n        <span class=\"dtag\">Dedicated Tenant<\/span>\n        <ul>\n          <li><b>Location:<\/b> isolated cloud instance in your region\/zone of choice<\/li>\n          <li><b>Data sovereignty:<\/b> very high, dedicated tenant<\/li>\n          <li><b>Hardware:<\/b> provided by the cloud provider, not by Parashift<\/li>\n          <li><b>Typical for:<\/b> regulated enterprises with their own cloud strategy<\/li>\n        <\/ul>\n      <\/div>\n      <div class=\"deploy-card\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l9 5-9 5-9-5 9-5Z\"\/><path d=\"M3 13l9 5 9-5\"\/><\/svg><\/div>\n        <h3>Parashift Plattform<\/h3>\n        <span class=\"dtag\">Coming soon<\/span>\n        <ul>\n          <li>Document Intelligence AI Guardrail Platform<\/li>\n          <li><b>Location:<\/b> Parashift's European sovereign cloud platform<\/li>\n          <li><b>Data sovereignty:<\/b> high, compliance zones EU, Switzerland, Germany<\/li>\n          <li><b>Additional features:<\/b> Ingestion, separation, validation, automation, 30+ connectors<\/li>\n          <li><b>Typical for:<\/b> teams who want to use the entire document pipeline<\/li>\n        <\/ul>\n      <\/div>\n      <div class=\"deploy-card\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M8 4L4 12l4 8\"\/><path d=\"M16 4l4 8-4 8\"\/><\/svg><\/div>\n        <h3>Dokumentli\u00ae API<\/h3>\n        <span class=\"dtag\">Coming soon<\/span>\n        <ul>\n          <li>Direct model cloud API access<\/li>\n          <li><b>Location:<\/b> programmatic endpoint, no platform UI<\/li>\n          <li><b>Hardware:<\/b> none, fully managed<\/li>\n          <li><b>Flexible:<\/b> against your own Dokumentli Node or a Parashift endpoint<\/li>\n          <li><b>Typical for:<\/b> teams embedding Dokumentli\u00ae into their own application<\/li>\n        <\/ul>\n      <\/div>\n    <\/div>\n    <div class=\"note brand\" style=\"margin-top:28px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M14.7 6.3a1 1 0 0 0 0 1.4l1.6 1.6a1 1 0 0 0 1.4 0l3.4-3.4a6 6 0 0 1-7.9 7.9L4.9 22 2 19.1l8.3-8.3a6 6 0 0 1 7.9-7.9l-3.4 3.4Z\"\/><\/svg><\/div>\n      <div><span class=\"kicker\">Vendor-Agnostic<\/span><h3>Open to any agentic automation and workflow solution<\/h3><p>On-prem, private cloud instance, and the Dokumentli\u00ae API can be connected to practically any document or workflow automation solution on the market \u2014 whether RPA, iPaaS, ERP, DMS, or a custom-built application. The only requirement is that the solution can make an API call; no binding to a specific platform is required.<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section>\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Usage &amp; Integration<\/span>\n      <h2>Fits into Your Existing Stack or the Parashift Platform<\/h2>\n      <p style=\"margin-top:20px;\">Dokumentli\u00ae is deliberately built to fit into virtually any existing document or workflow automation landscape, regardless of the deployment option chosen. In addition, Dokumentli\u00ae can be integrated in two fundamental ways.<\/p>\n    <\/div>\n    <div class=\"decision-grid\">\n      <div class=\"decision plain\">\n        <div class=\"miniflow\">\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"5\" y=\"4\" width=\"14\" height=\"17\" rx=\"1.5\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M8 4L4 12l4 8\"\/><path d=\"M16 4l4 8-4 8\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"6\" y=\"6\" width=\"12\" height=\"12\" rx=\"2\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"3.5\" y=\"5.5\" width=\"17\" height=\"13\" rx=\"1.5\"\/><\/svg><\/div>\n        <\/div>\n        <span class=\"kicker\">Direct Integration<\/span>\n        <h3>Programmatic, into any existing solution<\/h3>\n        <ul class=\"plain\">\n          <li><b>Full control:<\/b> Dokumentli\u00ae as a building block in your ERP, DMS, RPA\/iPaaS solution, or your own application.<\/li>\n          <li><b>Your own schema:<\/b> the request defines the desired data format.<\/li>\n          <li><b>Vendor-agnostic:<\/b> no binding to a specific platform, just one API call needed.<\/li>\n        <\/ul>\n      <\/div>\n      <div class=\"decision plain\">\n        <div class=\"miniflow\">\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 3h7l4 4v13a1 1 0 0 1-1 1H7a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1Z\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l9 5-9 5-9-5 9-5Z\"\/><path d=\"M3 13l9 5 9-5\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"6\" y=\"6\" width=\"12\" height=\"12\" rx=\"2\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"9\"\/><path d=\"M8 12.5l2.5 2.5L16 9.5\"\/><\/svg><\/div>\n          <span class=\"mf-arrow\">\u2192<\/span>\n          <div class=\"mf-node\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M4 12h4l2 3h4l2-3h4\"\/><path d=\"M4 12V6a1 1 0 0 1 1-1h14a1 1 0 0 1 1 1v6\"\/><path d=\"M4 12v6a1 1 0 0 0 1 1h14a1 1 0 0 0 1-1v-6\"\/><\/svg><\/div>\n        <\/div>\n        <span class=\"kicker\">Optional: Workflow Solution<\/span>\n        <h3>Additionally orchestrated via the Parashift Platform<\/h3>\n        <ul class=\"plain\">\n          <li><b>For anyone who doesn't want to run their own orchestration:<\/b> a built-in validation interface, human-in-the-loop without building your own frontend.<\/li>\n          <li><b>30+ connectors:<\/b> ERP, DMS, CRM systems, and email, without your own middleware.<\/li>\n          <li><b>Governance included:<\/b> Confidence scores, routing thresholds, audit trail, 2-\/3-way match.<\/li>\n        <\/ul>\n      <\/div>\n    <\/div>\n    <p style=\"margin-top:32px;color:var(--ink-soft);font-size:15.5px;max-width:76ch;\">In practice, this isn't an either-or decision: existing document and workflow automation solutions integrate Dokumentli\u00ae directly via the API, while teams without their own orchestration can additionally use the ready-made Parashift Platform. Both patterns can be combined on the same Dokumentli\u00ae instance.<\/p>\n    <p class=\"intchain\">RPA \u00b7 iPaaS \u00b7 ERP \u00b7 DMS \u00b7 CRM \u00b7 Email inboxes \u00b7 Custom applications<\/p>\n  <\/div>\n<\/section>\n\n<section class=\"alt\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Cost Logic<\/span>\n      <h2>Why Dokumentli\u00ae Is More Cost-Effective Than General-Purpose LLM APIs<\/h2>\n      <p>General-purpose frontier models at cloud providers are typically billed per API call and per token processed. For companies with high and fluctuating document volumes, this creates two structural disadvantages: costs scale directly with volume, with no predictable ceiling, and additionally with the context budget a general-purpose model requires per request.<\/p>\n    <\/div>\n    <div class=\"costcard\">\n      <div class=\"cc-head\">\n        <h3>Cost trend over time, schematic illustration<\/h3>\n        <p>Illustrative, without specific amounts: pay-per-call costs fluctuate with volume and demand spikes; a page-quota subscription stays constant and predictable.<\/p>\n      <\/div>\n      <div class=\"costlegend\">\n        <span><i class=\"ppc\"><\/i>Pay-per-call (general-purpose LLM API)<\/span>\n        <span><i class=\"sub\"><\/i>Dokumentli\u00ae (subscription)<\/span>\n        <span class=\"cost-flag\">Cost, axis illustrative \u2193<\/span>\n      <\/div>\n      <div class=\"costchart\">\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:70px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:115px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:45px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:138px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:80px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n        <div class=\"cgroup\"><div class=\"cbar ppc\" style=\"height:122px\"><\/div><div class=\"cbar sub\" style=\"height:88px\"><\/div><\/div>\n      <\/div>\n      <div class=\"costaxis\">\n        <span>Month 1<\/span><span>Month 2<\/span><span>Month 3<\/span><span>Month 4<\/span><span>Month 5<\/span><span>Month 6<\/span>\n      <\/div>\n    <\/div>\n    <div class=\"grid3\" style=\"grid-template-columns:1fr 1fr;margin-top:22px;\">\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"9\" cy=\"9\" r=\"5.5\"\/><circle cx=\"15\" cy=\"15\" r=\"5.5\"\/><\/svg><\/div>\n        <h3>Pay-per-call<\/h3>\n        <p>General-purpose LLM APIs: costs rise directly and without a ceiling as volume and token usage increase.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M12 3l7 3.5v5c0 4.8-3 8.6-7 9.5-4-.9-7-4.7-7-9.5v-5L12 3Z\"\/><path d=\"M9 12.2l2.1 2.1L15.5 10\"\/><\/svg><\/div>\n        <h3>Capacity-Based<\/h3>\n        <p>Dokumentli\u00ae: subscription with a page quota, predictable in advance, independent of demand spikes.<\/p>\n      <\/div>\n    <\/div>\n    <p style=\"margin-top:28px;color:var(--ink-soft);font-size:15.5px;max-width:76ch;\">This can be objectively measured through the lower compute per document: Dokumentli\u00ae processes a document with noticeably less compute power than general-purpose reference models, while achieving higher accuracy \u2013 and can run fully on a single consumer GPU with <b class=\"mono\" style=\"color:var(--ink)\">24 GB<\/b> VRAM instead of cloud data centers. That makes costs fundamentally predictable, independent of any individual cloud provider's pricing model.<\/p>\n    <div class=\"note plain\" style=\"margin-top:22px;\">\n      <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"9\" cy=\"9\" r=\"5.5\"\/><circle cx=\"15\" cy=\"15\" r=\"5.5\"\/><\/svg><\/div>\n      <div><h3 style=\"color:var(--ink)\">Subscriptions<\/h3><p style=\"color:var(--ink-soft)\">Dokumentli\u00ae is offered in several subscription tiers, scaled by monthly document volume, from pilot projects to high-volume enterprise deployment. Each tier includes <b style=\"color:var(--ink)\">4 base-model updates per year<\/b>, so accuracy and feature improvements flow in automatically, with no new contract.<\/p><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"deep\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\" style=\"background:rgba(73,135,245,.18);color:#7dabf9;border-color:rgba(73,135,245,.3)\">Trust &amp; Enterprise Readiness<\/span>\n      <h2>Trust That Goes Beyond Compliance<\/h2>\n    <\/div>\n    <div class=\"grid3 compliance\">\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"5\" y=\"10.5\" width=\"14\" height=\"10\" rx=\"1.5\"\/><path d=\"M8 10.5V7a4 4 0 1 1 8 0v3.5\"\/><\/svg><\/div>\n        <h3>Data Sovereignty<\/h3>\n        <p>Operation on-prem, air-gapped, or in dedicated compliance zones for the EU, Switzerland, and Germany \u2013 your document data never leaves the chosen zone.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M3 3l18 18\"\/><path d=\"M10.6 5.2A10.8 10.8 0 0 1 12 5c5 0 9 4 10.5 7-.6 1.2-1.5 2.5-2.7 3.7M6.1 6.9C4 8.3 2.4 10.2 1.5 12c1.5 3 5.5 7 10.5 7 1.4 0 2.7-.3 3.9-.8\"\/><path d=\"M9.9 10a3 3 0 0 0 4.2 4.2\"\/><\/svg><\/div>\n        <h3>No Shadow AI<\/h3>\n        <p>Dedicated tenants instead of shared infrastructure: your confidential documents never flow into publicly accessible model training.<\/p>\n      <\/div>\n      <div class=\"case\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M9 2v5\"\/><path d=\"M15 2v5\"\/><path d=\"M6.5 7h11a1.5 1.5 0 0 1 1.5 1.5V11a5 5 0 0 1-5 5h-4a5 5 0 0 1-5-5V8.5A1.5 1.5 0 0 1 6.5 7Z\"\/><path d=\"M12 16v3a3 3 0 0 1-3 3\"\/><\/svg><\/div>\n        <h3>Governance &amp; Audit Trail<\/h3>\n        <p>Confidence scores, routing thresholds, and complete audit trails on the Parashift Platform, for traceable decisions at every process step.<\/p>\n      <\/div>\n    <\/div>\n    <div class=\"compliance-badges\">\n      <span class=\"badges-label\">Certifications &amp; Audits<\/span>\n      <div class=\"badges-row\">\n        <span class=\"badge-logo\"><img decoding=\"async\" src=\"https:\/\/parashift.ai\/wp-content\/uploads\/2025\/11\/ISO27001-certified-500x500-1.png\" alt=\"ISO 27001\"><\/span>\n        <span class=\"badge-logo\"><img decoding=\"async\" src=\"https:\/\/parashift.ai\/wp-content\/uploads\/2025\/11\/AICPA-SOC-2-500x500-1.png\" alt=\"SOC 2\"><\/span>\n        <span class=\"badge-logo\"><img decoding=\"async\" src=\"https:\/\/parashift.ai\/wp-content\/uploads\/2025\/11\/Cloud-Computing-C5-500x500-1.png\" alt=\"BSI C5\"><\/span>\n        <span class=\"badge-logo\"><img decoding=\"async\" src=\"https:\/\/parashift.ai\/wp-content\/uploads\/2025\/11\/PCI-DSS-Compliant-500x500-1.avif\" alt=\"PCI DSS\"><\/span>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section>\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Conclusion &amp; Sources<\/span>\n      <h2>A Specialized Model for a Clearly Defined Task<\/h2>\n    <\/div>\n    <div class=\"usecase-feature\" style=\"margin-bottom:0;background:var(--bg-deep);border:none;\">\n      <div style=\"width:100%;\">\n        <p style=\"color:var(--invert-soft);font-size:16px;max-width:76ch;margin-bottom:24px;\">Dokumentli\u00ae achieves the highest average extraction accuracy among seven models tested, and is also the fastest model in the field on average \u2013 with significantly lower compute and the option to run fully air-gapped on a single consumer GPU with 24 GB VRAM.<\/p>\n        <div class=\"grid4\">\n          <div class=\"deploy-card\" style=\"padding:20px;\">\n            <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"12\" cy=\"12\" r=\"9\"\/><path d=\"M8 12.5l2.5 2.5L16 9.5\"\/><\/svg><\/div>\n            <h3 style=\"font-size:15px;margin-bottom:4px;\">More accurate<\/h3>\n            <p style=\"color:var(--invert-soft);font-size:13.5px;\">than general-purpose LLMs<\/p>\n          <\/div>\n          <div class=\"deploy-card\" style=\"padding:20px;\">\n            <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"6\" y=\"6\" width=\"12\" height=\"12\" rx=\"2\"\/><path d=\"M9 3v3M15 3v3M9 18v3M15 18v3M3 9h3M3 15h3M18 9h3M18 15h3\"\/><\/svg><\/div>\n            <h3 style=\"font-size:15px;margin-bottom:4px;\">Faster<\/h3>\n            <p style=\"color:var(--invert-soft);font-size:13.5px;\">than general-purpose LLMs<\/p>\n          <\/div>\n          <div class=\"deploy-card\" style=\"padding:20px;\">\n            <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><circle cx=\"9\" cy=\"9\" r=\"5.5\"\/><circle cx=\"15\" cy=\"15\" r=\"5.5\"\/><\/svg><\/div>\n            <h3 style=\"font-size:15px;margin-bottom:4px;\">More cost-effective<\/h3>\n            <p style=\"color:var(--invert-soft);font-size:13.5px;\">to operate<\/p>\n          <\/div>\n          <div class=\"deploy-card\" style=\"padding:20px;\">\n            <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"5\" y=\"10.5\" width=\"14\" height=\"10\" rx=\"1.5\"\/><path d=\"M8 10.5V7a4 4 0 1 1 8 0v3.5\"\/><\/svg><\/div>\n            <h3 style=\"font-size:15px;margin-bottom:4px;\">Air-gapped<\/h3>\n            <p style=\"color:var(--invert-soft);font-size:13.5px;\">on 1 GPU (24 GB)<\/p>\n          <\/div>\n        <\/div>\n      <\/div>\n    <\/div>\n    <div class=\"linkcards\">\n      <a class=\"linkcard\" href=\"#benchmarks\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M9 12.5l2 2 4-4.5\"\/><circle cx=\"12\" cy=\"12\" r=\"9\"\/><\/svg><\/div>\n        <div><h4>Read the Benchmark Report<\/h4><p>Full results by industry and model, confidence intervals, and methodology.<\/p><span class=\"go\">Request \u2192<\/span><\/div>\n      <\/a>\n      <a class=\"linkcard\" href=\"https:\/\/playground.parashift.io\/\" target=\"_blank\" rel=\"noopener\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><rect x=\"6\" y=\"6\" width=\"12\" height=\"12\" rx=\"2\"\/><path d=\"M9 3v3M15 3v3M9 18v3M15 18v3M3 9h3M3 15h3M18 9h3M18 15h3\"\/><\/svg><\/div>\n        <div><h4>Test the model<\/h4><p>Try your own documents at playground.parashift.io.<\/p><span class=\"go\">Open playground \u2192<\/span><\/div>\n      <\/a>\n      <a class=\"linkcard\" href=\"https:\/\/dokumentli-docs.parashift.io\/\" target=\"_blank\" rel=\"noopener\">\n        <div class=\"icon\"><svg viewBox=\"0 0 24 24\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.6\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M7 3h7l4 4v13a1 1 0 0 1-1 1H7a1 1 0 0 1-1-1V4a1 1 0 0 1 1-1Z\"\/><path d=\"M14 3v4h4\"\/><path d=\"M9 12h6\"\/><path d=\"M9 15.5h6\"\/><\/svg><\/div>\n        <div><h4>Documentation<\/h4><p>Technical details at dokumentli-docs.parashift.io.<\/p><span class=\"go\">Open docs \u2192<\/span><\/div>\n      <\/a>\n    <\/div>\n  <\/div>\n<\/section>\n\n<section class=\"alt\">\n  <div class=\"wrap\">\n    <div class=\"section-head\">\n      <span class=\"eyebrow\">Frequently Asked Questions<\/span>\n      <h2>What Automation Leads Ask Us First<\/h2>\n    <\/div>\n    <div class=\"faq\">\n      <div class=\"faqitem open\">\n        <button class=\"q\" type=\"button\">\n          <span>Can Dokumentli\u00ae really be used fully air-gapped?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>Yes. In the on-prem \/ own hardware deployment option, Dokumentli\u00ae runs in your own data center via the Dokumentli\u00ae Node \u2014 no data leaves your own network, and a single consumer-grade GPU with 24 GB VRAM is enough. Neither an additional data center nor an internet connection is required.<\/p><\/div>\n      <\/div>\n      <div class=\"faqitem\">\n        <button class=\"q\" type=\"button\">\n          <span>How was the 88.4% accuracy measured?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>In an independent test across 5 benchmark datasets comprising a total of 3,368 real business documents, against seven models including Dokumentli\u00ae, using cANLS@0.8 (Average Normalized Levenshtein Similarity with a threshold of 0.8) as the quality metric. The full methodology and detailed results are documented in the separate Benchmark Report.<\/p><\/div>\n      <\/div>\n      <div class=\"faqitem\">\n        <button class=\"q\" type=\"button\">\n          <span>Can Dokumentli\u00ae be combined with our existing LLM setup?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>Yes \u2014 combinable, not exclusive. Many companies use Dokumentli\u00ae specifically for inbound document processing and combine it, where needed, with general-purpose models for downstream steps unrelated to documents, such as open-ended reasoning or code.<\/p><\/div>\n      <\/div>\n      <div class=\"faqitem\">\n        <button class=\"q\" type=\"button\">\n          <span>How is Dokumentli\u00ae billed?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>Via a subscription with a page quota instead of pay-per-call, scaled by monthly document volume from pilot projects to high-volume deployment. Each tier includes 4 base-model updates per year, with no new contract.<\/p><\/div>\n      <\/div>\n      <div class=\"faqitem\">\n        <button class=\"q\" type=\"button\">\n          <span>What deployment options are available?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>Four: on-prem \/ own hardware and private cloud instance are available today; the Parashift Platform and the Dokumentli\u00ae API are coming soon. All four can be connected to practically any document or workflow automation solution.<\/p><\/div>\n      <\/div>\n      <div class=\"faqitem\">\n        <button class=\"q\" type=\"button\">\n          <span>What can't Dokumentli\u00ae do?<\/span>\n          <span class=\"plus\">+<\/span>\n        <\/button>\n        <div class=\"a\"><p>Dokumentli\u00ae is not a general-purpose assistant: for open-ended reasoning, code generation, general knowledge questions, free-form creative writing, or multi-step agentic tasks unrelated to documents, a general-purpose model is the right choice.<\/p><\/div>\n      <\/div>\n    <\/div>\n  <\/div>\n<\/section>\n<script type=\"application\/ld+json\">\n{\n  \"@context\": \"https:\/\/schema.org\",\n  \"@type\": \"FAQPage\",\n  \"mainEntity\": [\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can Dokumentli\u00ae really be used fully air-gapped?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Ja. In der Einsatzoption On-Prem \/ Own Hardware l\u00e4uft Dokumentli\u00ae im eigenen Rechenzentrum \u00fcber den Dokumentli\u00ae Node, no data leaves your own network, und eine einzelne konsumenten-taugliche GPU mit 24 GB VRAM reicht aus.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How was the 88.4% accuracy measured?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"In einem unabh\u00e4ngigen Test auf 5 Benchmark-Datens\u00e4tzen mit insgesamt 3'368 realen Gesch\u00e4ftsdokumenten, gegen sieben Modelle inklusive Dokumentli\u00ae, mit cANLS@0.8 als G\u00fctema\u00df.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"Can Dokumentli\u00ae be combined with our existing LLM setup?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Ja, kombinierbar statt exklusiv. Dokumentli\u00ae wird f\u00fcr die Dokumenteneingangsverarbeitung eingesetzt und l\u00e4sst sich mit general-purpose Modellen f\u00fcr nachgelagerte, dokumentfremde Schritte kombinieren.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"How is Dokumentli\u00ae billed?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"\u00dcber ein Abonnement mit Seitenkontingent statt Pay-per-call, gestaffelt nach monatlichem Dokumentenvolumen, inklusive 4 base-model updates per year.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What deployment options are available?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Vier: On-Prem \/ Own Hardware und Private Cloud Instance sind heute verf\u00fcgbar, die Parashift Plattform und die Dokumentli API folgen demn\u00e4chst.\"\n      }\n    },\n    {\n      \"@type\": \"Question\",\n      \"name\": \"What can't Dokumentli\u00ae do?\",\n      \"acceptedAnswer\": {\n        \"@type\": \"Answer\",\n        \"text\": \"Dokumentli ist kein general-purpose Assistent: f\u00fcr freies Reasoning, Code-Generierung, allgemeine Wissensfragen, freies kreatives Schreiben oder dokumentfremde Agenten-Taskn ist ein general-purpose Modell die richtige Wahl.\"\n      }\n    }\n  ]\n}\n<\/script>\n\n<section>\n  <div class=\"wrap\">\n    <div class=\"finalcta\">\n      <h2>Test Dokumentli\u00ae on your own documents.<\/h2>\n      <p>30 seconds in the playground show more than any slide: upload one of your own documents and see how Dokumentli\u00ae reads, classifies, and structures it.<\/p>\n      <div class=\"ctas\">\n        <a class=\"btn\" href=\"https:\/\/playground.parashift.io\/\" target=\"_blank\" rel=\"noopener\">Test the model in the playground<\/a>\n        <a class=\"btn ghost\" href=\"\/de\/demo\/\">Book a 30-min demo<\/a>\n      <\/div>\n      <div><span class=\"cite\">Benchmark Report on request \u00b7 Documentation at dokumentli-docs.parashift.io<\/span><\/div>\n    <\/div>\n  <\/div>\n<\/section>\n\n<\/div>\n\n<script>\n(function(){\n  var items = document.querySelectorAll('.psvr-scope .faqitem .q');\n  for (var i = 0; i < items.length; i++){\n    items[i].addEventListener('click', function(){\n      this.closest('.faqitem').classList.toggle('open');\n    });\n  }\n  if (window.matchMedia && matchMedia('(prefers-reduced-motion: reduce)').matches){\n    document.querySelectorAll('.psvr-scope .mv-svg').forEach(function(svg){\n      if (svg.pauseAnimations) svg.pauseAnimations();\n    });\n  }\n})();\n<\/script>\n\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t<\/section>\n\t\t\t\t<\/div>\n\t\t","protected":false},"excerpt":{"rendered":"","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"content-type":"","footnotes":""},"class_list":["post-51569","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/pages\/51569","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/comments?post=51569"}],"version-history":[{"count":1,"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/pages\/51569\/revisions"}],"predecessor-version":[{"id":51570,"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/pages\/51569\/revisions\/51570"}],"wp:attachment":[{"href":"https:\/\/parashift.ai\/en\/wp-json\/wp\/v2\/media?parent=51569"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}