const { useState, useEffect, useRef, useMemo, useCallback } = React; /* ============ DATA ============ */ const PILLARS = [ { id:'synthetic', idx:'01', name:'Synthetic Media', tag:'Deepfakes · Voice Clones · Generated Images', blurb:'Forensic-grade analysis across video, image, and audio — including live streams, not just uploaded files.', signals:['Face-swap forensics','Voice-clone forensics','Generated image artifacts','Live-stream deepfake analysis'] }, { id:'identity', idx:'02', name:'Synthetic Identity', tag:'Fake Accounts · Bots · Coordinated Networks', blurb:'Behavioral graphs and identity-coherence scoring expose bot farms and inauthentic persona networks at the account, network, and infrastructure level.', signals:['Identity coherence score','Behavioral fingerprints','Cross-platform linking','Infrastructure clustering'] }, { id:'language', idx:'03', name:'Language Forensics', tag:'AI-Written Text · Misinformation · Narratives', blurb:'Detects machine-generated text, traces narrative propagation, and maps coordinated messaging campaigns across 40+ languages.', signals:['Machine-text classifier','Narrative tracking','Campaign clustering','Semantic manipulation'] }, { id:'criminal', idx:'04', name:'Criminal Signals', tag:'Trafficking · Fraud · Radicalisation', blurb:'Signal-fusion layer that surfaces organised criminal activity hidden within ordinary platform traffic — ethically reviewed before any escalation.', signals:['Trafficking lexicons','Romance & investment fraud','Radicalisation pathways','Extortion patterns'] }, { id:'illegal', idx:'05', name:'Illegal Content', tag:'CSAM · NCII · Deepfake Pornography', blurb:'Hash-only, zero-knowledge evidence handling for the most sensitive content categories. Content is never stored or processed by the platform.', signals:['Perceptual hash matching','AI-generated CSAM detection','Non-consensual imagery','Trauma-informed workflow'] }, { id:'monitor', idx:'06', name:'Live Operations', tag:'Real-Time Dashboard · Case Management · Evidence', blurb:'The operational layer: a unified dashboard, case workflow, and evidence pipeline that turns detections into defensible action.', signals:['Live threat feed','Case management','Alert routing','Evidence packaging'] }, ]; const MOAT = [ { k:'01', t:'Unified Threat Graph', d:'Every signal from every pillar writes to one continuously-updated graph. What appears as six separate alerts elsewhere is resolved into a single coordinated operation here.' }, { k:'02', t:'Compound Threat Scoring', d:'Single-signal alerts mean noise. DeepShield escalates only when the graph shows convergence across multiple pillars — dramatically higher signal, dramatically fewer false positives.' }, { k:'03', t:'Model Attribution', d:'We don\'t just say content is synthetic. We identify the family of the generator that produced it — linking separate incidents back to shared adversary infrastructure.' }, { k:'04', t:'Forensic Evidence by Default', d:'Every decision is cryptographically anchored the moment it is made. Our output is admissible evidence — not a dashboard screenshot.' }, { k:'05', t:'Native-Language at Core', d:'40+ languages modelled natively, not machine-translated. Non-English manipulation is not a footnote — it is where most of the action is.' }, { k:'06', t:'Sovereign Deployment', d:'Full air-gapped operation inside a government or enterprise perimeter. No data egress. No third-party cloud dependency.' }, ]; const JURISDICTIONS = [ { code:'EU', law:'Digital Services Act' }, { code:'IN', law:'IT Act 2000' }, { code:'UK', law:'Online Safety Act' }, { code:'US', law:'Federal Rules of Evidence' }, { code:'SG', law:'POFMA' }, { code:'AU', law:'Online Safety Act 2021' }, ]; const METRICS = [ { v:'6', u:'intelligence pillars', l:'correlated in one graph' }, { v:'40+', u:'languages', l:'natively modelled' }, { v:'<1s', u:'critical-signal latency', l:'hash & live-stream tier' }, { v:'6', u:'regulatory regimes', l:'evidence-package ready' }, ]; /* Scan subjects — each has a synthetic SVG face + ground truth */ const SUBJECTS = [ { id:'SBJ-A41', verdict:'AUTHENTIC', conf:0.97, model:null, hue:35, face:'f1', signals:{ geo:0.04, tex:0.06, rppg:0.91, temp:0.03, prov:0.98 }, attr:'Camera-captured · EXIF verified', loc:'Manchester, UK' }, { id:'SBJ-B18', verdict:'DEEPFAKE', conf:0.94, model:'Face-Swap · family A', hue:200, face:'f2', signals:{ geo:0.83, tex:0.77, rppg:0.12, temp:0.69, prov:0.22 }, attr:'Face-swap boundary artifacts · rPPG absent', loc:'São Paulo, BR' }, { id:'SBJ-C07', verdict:'SYNTHETIC', conf:0.89, model:'Diffusion · family C', hue:280, face:'f3', signals:{ geo:0.71, tex:0.88, rppg:0.04, temp:0.41, prov:0.08 }, attr:'Fully generated image · frequency signature detected', loc:'Dubai, AE' }, { id:'SBJ-D29', verdict:'AUTHENTIC', conf:0.93, model:null, hue:150, face:'f4', signals:{ geo:0.09, tex:0.08, rppg:0.86, temp:0.07, prov:0.92 }, attr:'Live capture · physiological signal present', loc:'Bengaluru, IN' }, { id:'SBJ-E63', verdict:'DEEPFAKE', conf:0.91, model:'Lip-sync · family B', hue:20, face:'f5', signals:{ geo:0.38, tex:0.32, rppg:0.44, temp:0.87, prov:0.35 }, attr:'Lip-audio desynchronisation · temporal breaks', loc:'Lagos, NG' }, { id:'SBJ-F12', verdict:'AUTHENTIC', conf:0.95, model:null, hue:330, face:'f6', signals:{ geo:0.05, tex:0.11, rppg:0.88, temp:0.06, prov:0.94 }, attr:'Broadcast source · chain-of-custody intact', loc:'Berlin, DE' }, ]; /* ============ SVG FACE ILLUSTRATIONS ============ */ function SyntheticFace({ variant='f1', hue=200 }){ const skin = `oklch(0.68 0.09 ${hue})`; const shade = `oklch(0.45 0.08 ${hue})`; const hair = `oklch(0.22 0.03 ${(hue+40)%360})`; const lip = `oklch(0.55 0.14 ${(hue+20)%360})`; const eye = `oklch(0.35 0.06 ${(hue+120)%360})`; const common = ( <> ); // 6 variants — different head/hair/jaw const V = { f1: (<> ), f2: (<> ), f3: (<> ), f4: (<> ), f5: (<> ), f6: (<> ), }; return ( {common} {V[variant]} ); } /* ============ LIVE FACE SCANNER ============ */ function FaceScanner(){ const [subjectIdx, setSubjectIdx] = useState(0); const [phase, setPhase] = useState(0); // 0 idle / 1 landmarks / 2 frequency / 3 rppg / 4 temporal / 5 verdict const [scanY, setScanY] = useState(0); const [landmarks, setLandmarks] = useState([]); const [freqBars, setFreqBars] = useState(Array(24).fill(0)); const [pulse, setPulse] = useState([]); const [log, setLog] = useState([]); const subject = SUBJECTS[subjectIdx]; // Phase timing: cycle through phases useEffect(()=>{ const ranges = [800, 1600, 1800, 1800, 1600, 2400]; // ms per phase let p = 0; setPhase(p); setLog([]); const advance = ()=>{ p += 1; if(p>5){ // next subject setSubjectIdx(i => (i+1) % SUBJECTS.length); return; } setPhase(p); const msgs = [ null, `>> FACE LOCK · 68 landmarks anchored · ${subject.id}`, `>> SPECTRAL SWEEP · DCT residuals · ${(subject.signals.tex*100).toFixed(0)}% anomaly`, `>> rPPG · blood-flow micro-signal · ${subject.signals.rppg>0.5?'present':'absent'}`, `>> TEMPORAL · frame coherence · ${(subject.signals.temp*100).toFixed(0)}% drift`, `>> VERDICT · ${subject.verdict} @ ${(subject.conf*100).toFixed(0)}%${subject.model? ' · '+subject.model:''}` ]; if(msgs[p]) setLog(L => [...L, { id:Math.random(), t:msgs[p], phase:p }]); timer = setTimeout(advance, ranges[p] || 2400); }; let timer = setTimeout(advance, ranges[0]); return ()=>clearTimeout(timer); }, [subjectIdx]); // Animated overlays per phase useEffect(()=>{ let raf, t=0; const tick = ()=>{ t += 1; // scan line 0-100 setScanY(prev => (prev + 1.2) % 100); // landmarks (phase 1+) if(phase>=1){ if(landmarks.length<38){ setLandmarks(L => L.length<38 ? [...L, randomLandmark(L.length)] : L); } } // freq bars (phase 2+) if(phase>=2){ setFreqBars(bars => bars.map((v,i)=>{ const target = (subject.signals.tex*0.6 + 0.2) * (0.5 + 0.5*Math.sin(t*0.1 + i*0.4)); return v + (Math.abs(target) - v) * 0.15 + (Math.random()-0.5)*0.03; })); } // pulse (phase 3+) if(phase>=3){ setPulse(p => { const val = subject.signals.rppg>0.5 ? 0.5 + 0.35*Math.sin(t*0.22) + (Math.random()-0.5)*0.05 : 0.5 + (Math.random()-0.5)*0.08; // flat-ish return [...p, val].slice(-80); }); } raf = requestAnimationFrame(tick); }; raf = requestAnimationFrame(tick); return ()=>cancelAnimationFrame(raf); }, [phase, subjectIdx]); // Reset visuals on subject change useEffect(()=>{ setLandmarks([]); setFreqBars(Array(24).fill(0)); setPulse([]); }, [subjectIdx]); const verdictColor = subject.verdict==='AUTHENTIC' ? 'oklch(0.78 0.17 145)' : subject.verdict==='DEEPFAKE' ? 'oklch(0.70 0.22 20)' : 'oklch(0.74 0.19 50)'; return (
{/* Header */}
LIVE · FACIAL FORENSICS SUBJECT {subject.id} · {subject.loc}
{['IDLE','LANDMARKS','SPECTRAL','rPPG','TEMPORAL','VERDICT'][phase]} · {phase+1}/6
{/* LEFT — face stage */}
{/* face */}
{/* reticle brackets */} {['tl','tr','bl','br'].map((k,i)=>(
=2?'2px solid var(--accent)':'none', borderLeft: i%2===0?'2px solid var(--accent)':'none', borderRight: i%2===1?'2px solid var(--accent)':'none', }}/> ))} {/* scan line */} {phase>0 && phase<5 && (
)} {/* landmarks */} {phase>=1 && ( {landmarks.map((l,i)=>( {l.link && landmarks[l.link] && ( )} ))} )} {/* verdict ring */} {phase===5 && (
)}
{/* overlay meta */}
▸ FACE ID: {subject.id}
▸ PIPELINE: PILLAR 01 · FORENSIC STACK
▸ FRAME: {(subjectIdx*347 + phase*53).toString().padStart(6,'0')}
{phase===5 && (
DEEPSHIELD VERDICT
{subject.verdict} · {(subject.conf*100).toFixed(0)}%
{subject.attr}
)} {/* pagination dots */}
{SUBJECTS.map((s,i)=>(
{/* RIGHT — telemetry */}
GEOMETRIC · TEXTURE · PROVENANCE
FREQUENCY SPECTRUM · DCT RESIDUALS
{freqBars.map((v,i)=>(
0.5?'oklch(0.70 0.22 20)':'var(--accent-2)'})`, opacity:0.85, borderRadius:1 }}/> ))}
rPPG · PHYSIOLOGICAL PULSE
`${(i/80)*200},${50-v*48}`).join(' ')} fill="none" stroke={subject.signals.rppg>0.5?'oklch(0.78 0.18 145)':'oklch(0.70 0.22 20)'} strokeWidth="1.2" />
PIPELINE LOG
{log.map(l=>(
{l.t}
))} {log.length===0 &&
awaiting lock...
}
{/* footer strip */}
SIMULATED LIVE SCAN · REFRESH 10s
EVIDENCE-HASH: 0x{(subject.id+phase).split('').reduce((a,c)=>((a*31+c.charCodeAt(0))>>>0), 7).toString(16).padStart(8,'0')}
); } function randomLandmark(i){ // fake 68-landmark positions roughly spread on a face oval const ring = [ {x:30,y:55},{x:28,y:62},{x:27,y:70},{x:29,y:78},{x:33,y:84},{x:40,y:88}, {x:50,y:90},{x:60,y:88},{x:67,y:84},{x:71,y:78},{x:73,y:70},{x:72,y:62},{x:70,y:55}, {x:38,y:50},{x:45,y:47},{x:55,y:47},{x:62,y:50}, {x:42,y:57},{x:48,y:56},{x:52,y:56},{x:58,y:57}, // eyes {x:50,y:63},{x:48,y:68},{x:52,y:68}, // nose {x:45,y:75},{x:50,y:77},{x:55,y:75}, // mouth {x:40,y:45},{x:60,y:45},{x:35,y:60},{x:65,y:60}, {x:46,y:73},{x:54,y:73},{x:44,y:79},{x:56,y:79}, {x:38,y:65},{x:62,y:65},{x:50,y:52}, ]; const p = ring[i%ring.length]; return { x: p.x + (Math.random()-0.5)*1.5, y: p.y + (Math.random()-0.5)*1.5, link: i>0? i-1 : null }; } function SigRow({ label, v, high, invert }){ // "high" threshold: red when v high (bad) unless invert const isBad = invert ? v<0.4 : v>0.5; const color = isBad ? 'oklch(0.70 0.22 20)' : 'oklch(0.78 0.17 145)'; return (
{label}
{(v*100).toFixed(0)}%
); } /* ============ 3D ORBIT HERO ============ */ function OrbitCore({ onSelect, selected }){ const wrapRef = useRef(); const [tilt, setTilt] = useState({x:-18, y:22}); const [hovered, setHovered] = useState(null); const speed = (window.__TWEAKS__?.rotateSpeed) || 28; useEffect(()=>{ const el = wrapRef.current; if(!el) return; const onMove = (e)=>{ const r = el.getBoundingClientRect(); const cx = r.left + r.width/2, cy = r.top + r.height/2; const dx = (e.clientX - cx)/r.width, dy = (e.clientY - cy)/r.height; setTilt({ x: -18 + dy*-14, y: 22 + dx*30 }); }; window.addEventListener('mousemove', onMove); return ()=>window.removeEventListener('mousemove', onMove); },[]); const nodes = PILLARS.map((p,i)=>({ ...p, a: (i/PILLARS.length)*Math.PI*2, i })); return (
{nodes.map((n)=>{ const cx = 50 + 50*Math.cos(n.a); const cy = 50 + 50*Math.sin(n.a); const active = selected === n.id || hovered === n.id; return ( ); })}
{Array.from({length:8}).map((_,i)=>(
))} {Array.from({length:4}).map((_,i)=>(
))}
{['TL','TR','BL','BR'].map((p,i)=>(
=2?'1px solid var(--line-2)':'none', borderLeft: i%2===0?'1px solid var(--line-2)':'none', borderRight: i%2===1?'1px solid var(--line-2)':'none', }}/> ))}
SYS://DEEPSHIELD.CORE
TG:// ACTIVE · 6 PILLARS
); } /* ============ THREAT GRAPH ============ */ function ThreatGraph(){ const canvasRef = useRef(); const stateRef = useRef(null); useEffect(()=>{ const c = canvasRef.current; if(!c) return; const dpr = Math.min(window.devicePixelRatio||1, 2); const resize = ()=>{ const r = c.getBoundingClientRect(); c.width = r.width*dpr; c.height = r.height*dpr; }; resize(); window.addEventListener('resize', resize); const W = ()=>c.width/dpr, H = ()=>c.height/dpr; const nodes = []; const pillarColors = ['#5fe3ff','#9ab4ff','#bde66c','#ffb36b','#ff7a8a','#c8a2ff']; PILLARS.forEach((p,i)=>{ nodes.push({ id:'P'+i, type:'pillar', idx:p.idx, label:p.name, color:pillarColors[i], x:0, y:0, r:14 }); }); for(let i=0;i<34;i++){ nodes.push({ id:'N'+i, type: Math.random()<0.3?'content':'account', x: Math.random()*600-300, y: Math.random()*400-200, vx:0, vy:0, r:3+Math.random()*2, flagged: Math.random()<0.55 ? Math.floor(Math.random()*6) : -1, }); } const edges = []; nodes.filter(n=>n.type!=='pillar').forEach(n=>{ if(n.flagged>=0) edges.push({a:'P'+n.flagged, b:n.id, strong:Math.random()<0.4}); if(Math.random()<0.4){ const other = nodes[6+Math.floor(Math.random()*34)]; if(other && other.id!==n.id) edges.push({a:other.id, b:n.id, strong:false}); } }); stateRef.current = { nodes, edges, t:0 }; const byId = Object.fromEntries(nodes.map(n=>[n.id,n])); let raf; const tick = ()=>{ const s = stateRef.current; s.t += 1; const w=W(), h=H(), cx=w/2, cy=h/2; nodes.filter(n=>n.type==='pillar').forEach((n,i)=>{ const a = (i/6)*Math.PI*2 - Math.PI/2 + s.t*0.0015; const R = Math.min(w,h)*0.36; n.x = cx + R*Math.cos(a); n.y = cy + R*Math.sin(a); }); const others = nodes.filter(n=>n.type!=='pillar'); for(const n of others){ n.vx += (cx - n.x)*0.0006; n.vy += (cy - n.y)*0.0006; if(n.flagged>=0){ const p = byId['P'+n.flagged]; const dx = p.x-n.x, dy = p.y-n.y; const d = Math.hypot(dx,dy)+0.01; const f = 0.0008*(d-90); n.vx += dx/d*f*100; n.vy += dy/d*f*100; } for(const m of others){ if(m===n) continue; const dx = n.x-m.x, dy = n.y-m.y; const d2 = dx*dx+dy*dy+40; const f = 60/d2; n.vx += dx*f*0.02; n.vy += dy*f*0.02; } n.vx *= 0.86; n.vy *= 0.86; n.x += n.vx; n.y += n.vy; } const ctx = c.getContext('2d'); ctx.setTransform(dpr,0,0,dpr,0,0); ctx.clearRect(0,0,w,h); ctx.strokeStyle = 'rgba(140,180,220,0.05)'; ctx.lineWidth = 1; for(let x=0;xe.strong)){ const A = byId[e.a], B = byId[e.b]; if(!A||!B) continue; const px = A.x + (B.x-A.x)*phase, py = A.y + (B.y-A.y)*phase; ctx.fillStyle = A.color || '#5fe3ff'; ctx.beginPath(); ctx.arc(px,py,2,0,Math.PI*2); ctx.fill(); } for(const n of others){ ctx.fillStyle = n.flagged>=0 ? (nodes[n.flagged].color) : 'rgba(200,210,225,0.5)'; ctx.globalAlpha = n.flagged>=0 ? 0.9 : 0.5; ctx.beginPath(); ctx.arc(n.x,n.y,n.r,0,Math.PI*2); ctx.fill(); } ctx.globalAlpha=1; for(const n of nodes.filter(n=>n.type==='pillar')){ const g = ctx.createRadialGradient(n.x,n.y,2,n.x,n.y,36); g.addColorStop(0, n.color+'88'); g.addColorStop(1, 'transparent'); ctx.fillStyle = g; ctx.beginPath(); ctx.arc(n.x,n.y,36,0,Math.PI*2); ctx.fill(); ctx.fillStyle = '#0a0e13'; ctx.strokeStyle = n.color; ctx.lineWidth = 1.5; ctx.beginPath(); ctx.arc(n.x,n.y,n.r,0,Math.PI*2); ctx.fill(); ctx.stroke(); ctx.fillStyle = n.color; ctx.font = '600 10px JetBrains Mono, monospace'; ctx.textAlign='center'; ctx.textBaseline='middle'; ctx.fillText(n.idx, n.x, n.y); ctx.fillStyle = 'rgba(200,215,230,0.85)'; ctx.font = '500 10px Inter, sans-serif'; ctx.fillText(n.label.toUpperCase(), n.x, n.y+26); } raf = requestAnimationFrame(tick); }; tick(); return ()=>{ cancelAnimationFrame(raf); window.removeEventListener('resize', resize); }; },[]); const [events, setEvents] = useState([]); useEffect(()=>{ const lines = [ ['P1+P2','face-swap + synth identity cluster flagged'], ['P3+P2','LLM narrative injected via bot ring'], ['P1+P5','deepfake pornography — hash match'], ['P4+P2','romance-fraud ring · 41 nodes'], ['P3','novel narrative emerged · cross-lang'], ['P1','live-stream deepfake · confidence 0.94'], ['P4+P3','radicalisation pathway · stage 3'], ['P2','coordinated engagement spike'], ]; const id = setInterval(()=>{ const l = lines[Math.floor(Math.random()*lines.length)]; const stamp = new Date().toISOString().substring(11,19); setEvents(ev => [{stamp, tag:l[0], msg:l[1], id:Math.random()}, ...ev].slice(0,8)); }, 1400); return ()=>clearInterval(id); },[]); return (
LIVE · THREAT GRAPH CPCE · compound scoring engaged
{new Date().toISOString().substring(0,10)}
EVENT FEED // LAST 8
{events.map(e=>(
{e.stamp} · {e.tag}
{e.msg}
))} {events.length===0 &&
awaiting signal...
}
); } /* ============ SECTIONS ============ */ function Nav(){ const [menuOpen, setMenuOpen] = useState(false); return ( ); } function Hero({ selected, setSelected }){ const p = PILLARS.find(p=>p.id===selected) || PILLARS[0]; return (
DIGITAL TRUTH OPERATING SYSTEM · GLOBAL

Truth at the speed
of synthetic.

DeepShield unifies six intelligence pillars — deepfake forensics, synthetic identity, language, criminal signals, illegal content, and live operations — into a single continuously-updated threat graph. One platform. One data model. Evidence-grade output.

{METRICS.map(m=>(
{m.v}
{m.u}
{m.l}
))}
{p.idx}
{p.name}
{p.tag}
inspect →
DASTUTE TECHNOLOGIES LIMITED · DIGITAL TRUTH OS
LAT: 12.9716°N · LON: 77.5946°E
); } function Pillars({ selected, setSelected }){ return (
§ 02 · ARCHITECTURE

Six pillars. One graph.

Every signal writes to a single threat graph — so a fake account, posting a deepfake, with AI-written copy, inside an illegal campaign, resolves as one operation.

{PILLARS.map(p=>{ const active = selected===p.id; return ( ); })}
); } function ScanSection(){ return (
§ 03 · LIVE FACIAL FORENSICS

Watch it decide,
frame by frame.

A continuous scan of rotating subjects. The pipeline locks geometry, probes spectral residuals, measures the physiological pulse the generator forgot, checks temporal coherence, and issues a verdict. What you see below is the operator view — not a marketing loop.
{[ {h:'68-point landmarks', d:'Geometric mesh reconstructed per frame to expose warping and swap boundaries.'}, {h:'Spectral residuals', d:'Frequency-domain signatures reveal artefacts invisible to the human eye.'}, {h:'rPPG pulse signal', d:'Natural micro blood-flow variations that synthetic pipelines cannot fake.'}, {h:'Temporal coherence', d:'Frame-to-frame consistency scoring — blinks, micro-expressions, lip-audio sync.'}, ].map(c=>(
{c.h}
{c.d}
))}
); } function GraphSection(){ return (
§ 04 · THE DIFFERENTIATOR

The Threat Graph, live.

Single-pillar alerts are noise. Convergence across multiple pillars is certainty. Below is a simulated view of what operators see — accounts, content, and infrastructure binding themselves to pillar signatures in real time.
); } function MoatSection(){ return (
§ 05 · WHY WE WIN

What no one else
can assemble.

Our moat isn't a single feature. It is the compounded value of these capabilities operating on one graph. To match it, a rival would have to simultaneously rebuild six domains of research and years of partnerships.
{MOAT.map((m,i)=>(
USP / {m.k}
{m.t}

{m.d}

))}
); } function WhoItsFor(){ const audiences = [ { t:'Governments & Regulators', d:'Sovereign, air-gapped deployment for national digital-safety authorities. Evidence output admissible under the local legal framework.', items:['DSA reporting', 'National CERT integration', 'Law-enforcement liaison'] }, { t:'Platforms & Publishers', d:'Trust & safety teams get a unified threat intelligence layer instead of six siloed vendors. API-first, webhook-native.', items:['Real-time webhooks', 'Case workflow', 'SLA-backed uptime'] }, { t:'Newsrooms & Broadcasters', d:'Verify source material before publication. Every check produces a cryptographic receipt that stays with the story.', items:['Provenance receipts', 'Pre-publication scan', 'Editorial dashboard'] }, { t:'Financial Institutions', d:'Stop romance fraud, investment scams, and deepfake KYC attempts before they convert into losses. Compliance-grade reports.', items:['Synthetic-identity flags', 'Liveness defence', 'Fraud case packaging'] }, ]; return (
§ 06 · WHO IT IS FOR

Infrastructure, not a vendor.

{audiences.map(a=>(
{a.t}

{a.d}

{a.items.map(it=>( {it} ))}
))}
); } function HowItWorks(){ const steps = [ { n:'01', t:'Ingest', d:'Content arrives via platform APIs, crawlers, or submissions. Each item gets a universal ID.' }, { n:'02', t:'Decompose', d:'The asset is broken into analysable signals — frames, tokens, voiceprints, network vectors.' }, { n:'03', t:'Detect', d:'Six pillar engines run in parallel. Each produces a confidence-scored signal on the event bus.' }, { n:'04', t:'Correlate', d:'The Threat Graph binds signals across pillars into compound-scored incidents in milliseconds.' }, { n:'05', t:'Evidence', d:'Every decision is cryptographically anchored. Packages are ready for jurisdiction-specific submission.' }, { n:'06', t:'Act', d:'Alerts route to operators, platforms, or law-enforcement partners via webhook, API, or dashboard.' }, ]; return (
§ 07 · HOW IT WORKS

From ingest to evidence in under a second.

{steps.map(s=>(
STEP {s.n}
{s.t}
{s.d}
))}
); } function DeploymentSection(){ const [mode, setMode] = useState('sovereign'); return (
§ 08 · DEPLOYMENT

Cloud, on-prem, or inside your perimeter.

{[ {id:'cloud', t:'Managed Cloud', d:'Multi-region, zero-ops. For platforms, publishers, and trust & safety teams that want detection-as-infrastructure.'}, {id:'sovereign', t:'Sovereign Air-Gap', d:'Fully on-premises, no data egress, no third-party dependency. Designed for governments, regulators, and law-enforcement agencies with data-sovereignty mandates.'}, ].map(m=>{ const active = mode===m.id; return ( ); })}
EVIDENCE-GRADE · JURISDICTIONS
{JURISDICTIONS.map(j=>(
{j.code}
{j.law}
))}
OPERATING PRINCIPLES · NON-NEGOTIABLE
    {[ 'Human review before any law-enforcement referral', 'No surveillance-as-a-service — ever', 'Quarterly bias audits across protected characteristics', 'Minimum-necessary data retention with deletion proofs', 'Illegal content never stored — only cryptographic evidence', ].map(x=>(
  • {x}
  • ))}
); } function Contact(){ return (
§ 09 · TALK TO US

Stand up a Digital Truth layer for your organisation.

Briefings cover platform architecture, jurisdictional evidence formats, and deployment options tailored to your operating environment.

CONTACT CHANNEL
General & partnerships
sanjay@dastute.co.uk
Operated by
Dastute Technologies Limited
); } function Footer(){ return (
DeepShield

A product of Dastute Technologies Limited. For partner and enterprise enquiries, get in touch.

{[ {h:'Platform', l:['Pillars','Live Scan','Threat Graph','Deployment']}, {h:'Company', l:['About','Principles','Partners','Press']}, {h:'Contact', l:['sanjay@dastute.co.uk','Request a briefing','Law-enforcement liaison']}, ].map(c=>(
{c.h}
    {c.l.map(x=>
  • {x}
  • )}
))}
© 2026 · DASTUTE TECHNOLOGIES LIMITED
ALL SYSTEMS NOMINAL
); } function Tweaks({ setAccentHue, accentHue, setSpeed, speed }){ const [open, setOpen] = useState(false); useEffect(()=>{ const onMsg = (e)=>{ if(e.data?.type==='__activate_edit_mode') setOpen(true); if(e.data?.type==='__deactivate_edit_mode') setOpen(false); }; window.addEventListener('message', onMsg); window.parent.postMessage({type:'__edit_mode_available'},'*'); return ()=>window.removeEventListener('message', onMsg); },[]); if(!open) return null; const set = (k,v)=>window.parent.postMessage({type:'__edit_mode_set_keys', edits:{[k]:v}}, '*'); return (
Tweaks
LIVE
ACCENT HUE · {accentHue}°
{const v=+e.target.value; setAccentHue(v); set('accentHue',v);}} style={{width:'100%'}} />
ORBIT SPEED · {speed}s
{const v=+e.target.value; setSpeed(v); set('rotateSpeed',v);}} style={{width:'100%'}} />
); } function App(){ const [selected, setSelected] = useState('synthetic'); const [accentHue, setAccentHue] = useState(window.__TWEAKS__?.accentHue || 215); const [speed, setSpeed] = useState(window.__TWEAKS__?.rotateSpeed || 28); useEffect(()=>{ document.documentElement.style.setProperty('--accent', `oklch(0.78 0.16 ${accentHue})`); },[accentHue]); useEffect(()=>{ window.__TWEAKS__.rotateSpeed = speed; },[speed]); return ( <>