const { useState, useEffect, useRef, useMemo } = React; /* ────────────────────────────────────────────────────────────────────────── */ /* ROOT */ /* ────────────────────────────────────────────────────────────────────────── */ function App() { return (
); } /* ────────────────────────────────────────────────────────────────────────── */ /* TOP TICKER */ /* ────────────────────────────────────────────────────────────────────────── */ function TopTicker() { const items = [ ['SOL/USD', '$184.62', '+2.41%'], ['HELIUS LATENCY', '47ms', null], ['EXEC P99', '128ms', null], ['MC RUNS · 24H', '1,284,000', null], ['NHL · SLATE-A', 'SETTLED', null], ['NBA · SLATE-B', 'LIVE', '+EV'], ['BTC/USD', '$72,108.40', '+1.18%'], ['ETH/USD', '$3,418.91', '-0.62%'], ['SMART WALLETS', '1,847 tracked', null], ['STOP-LOSS POLICY', 'σ=5.00%', null], ['MLB · SLATE-C', 'PRE-LOCK', null], ['LOG5 MATRIX', 'NIGHTLY 03:00Z', null], ]; const row = [...items, ...items]; return (
{row.map((it, i) => (
{it[0]} {it[1]} {it[2] && ( {it[2]} )} ·
))}
); } /* ────────────────────────────────────────────────────────────────────────── */ /* NAV */ /* ────────────────────────────────────────────────────────────────────────── */ function Logo({ size = 22 }) { return ( ); } function Nav() { return ( ); } /* ────────────────────────────────────────────────────────────────────────── */ /* HERO */ /* ────────────────────────────────────────────────────────────────────────── */ function Hero() { return (
{/* Left: copy */}
[ SQA · INSTITUTIONAL TIER / RUNTIME OPERATIONAL ]

Institutional
Quantitative
Infrastructure.

We build AI-driven, high-frequency quantitative simulation engines for{' '} decentralized finance and{' '} predictive sports modeling.

{/* footer stat row */}
{[ ['127ms', 'P50 execution'], ['10,000×', 'MC iterations / slate'], ['1,847', 'Smart wallets indexed'], ['σ 5.00%', 'Stop-loss policy'], ].map(([n, l]) => (
{n}
{l}
))}
{/* Right: live system panel */}
); } function HeroSystemPanel() { const [tick, setTick] = useState(0); useEffect(() => { const t = setInterval(() => setTick(x => x + 1), 1100); return () => clearInterval(t); }, []); // Synthetic latency series, deterministic seeded const series = useMemo(() => { return Array.from({ length: 48 }, (_, i) => { const s = Math.sin(i * 0.41) * 0.5 + Math.cos(i * 0.92) * 0.3; return 0.45 + s * 0.18 + (i % 11 === 0 ? 0.12 : 0); }); }, []); const latency = 118 + (tick % 7) * 3 - 6; const queue = 312 + (tick % 13); return (
Runtime · us-east-1
v4.21.8
Exec latency
{latency} ms
P50 · trailing 60s
Queue depth
{queue} msg
Helius WS · stable
{/* sparkline */}
{series.map((v, i) => (
series.length - 6 ? 'rgba(103,232,249,0.55)' : 'rgba(255,255,255,0.16)', }} /> ))}
−60s−30snow
{[ ['Helius', 'OK', 'emerald'], ['Solana', 'OK', 'emerald'], ['Reasoner', 'OK', 'emerald'], ].map(([k, v]) => (
{k} {v}
))}
{/* corner ticks */}
); } function CornerTicks() { return ( <>
); } /* ────────────────────────────────────────────────────────────────────────── */ /* ARCHITECTURE — BENTO */ /* ────────────────────────────────────────────────────────────────────────── */ function SectionHeader({ index, eyebrow, title, kicker }) { return (
§{index} / {eyebrow}

{title}

{kicker && (

{kicker}

)}
); } function Architecture() { return (
); } /* ───── SOL SENTINEL CARD ───── */ function SolSentinelCard() { return (
{/* header */}
◆ Card 01 · On-chain Execution
LIVE · mainnet-beta

SOL Sentinel

High-frequency algorithmic trading on the Solana blockchain. Real-time Helius API tracking of smart-money wallet movements and liquidity pools. Features automated "Kevin's Ladder" execution logic with strict 5% dynamic stop-losses for unmonitored overnight market volatility.

{/* internal bento */}
); } function WalletTracker() { const seed = [ { w: '7gKx…Hp4f', tag: 'whale · t1', qty: '+12,400 SOL', side: 'BUY', pool: 'BONK/SOL', ms: 12 }, { w: 'B2qN…M9Lz', tag: 'mm · jump', qty: '−3,200 SOL', side: 'SELL', pool: 'WIF/SOL', ms: 18 }, { w: 'Cf4R…s12p', tag: 'whale · t1', qty: '+8,910 SOL', side: 'BUY', pool: 'JUP/USDC', ms: 9 }, { w: 'Dm9X…aQ7t', tag: 'inflow · cex', qty: '+24,800 SOL', side: 'BUY', pool: 'SOL/USDC', ms: 31 }, { w: 'Eq1V…r3Yk', tag: 'whale · t2', qty: '+1,180 SOL', side: 'BUY', pool: 'POPCAT', ms: 14 }, { w: 'Fa0L…u8Wm', tag: 'dev · multisig',qty: '−540 SOL', side: 'SELL', pool: 'TNSR', ms: 22 }, ]; const [rows, setRows] = useState(seed); useEffect(() => { const id = setInterval(() => { setRows(prev => { const next = [...prev]; // rotate const head = next.shift(); next.push({ ...head, ms: 6 + Math.floor(Math.random() * 28), qty: head.qty, }); return next; }); }, 1800); return () => clearInterval(id); }, []); return (
Smart-money feed · Helius WS
last 60s
wallet
tag
qty
pool
Δ
{rows.map((r, i) => (
{r.w}
{r.tag}
{r.qty}
{r.pool}
{r.ms}ms
))}
); } function KevinsLadder() { // 6 rungs representing scaled entry/exit ladder const rungs = [ { px: '$184.62', size: '25%', state: 'fill', d: '+0.0%' }, { px: '$182.30', size: '20%', state: 'fill', d: '−1.3%' }, { px: '$179.84', size: '20%', state: 'arm', d: '−2.6%' }, { px: '$177.05', size: '15%', state: 'arm', d: '−4.1%' }, { px: '$175.39', size: '12%', state: 'pend', d: '−5.0%' }, { px: '$172.20', size: '08%', state: 'pend', d: '−6.7%' }, ]; const [active, setActive] = useState(2); useEffect(() => { const id = setInterval(() => setActive(a => (a + 1) % rungs.length), 1500); return () => clearInterval(id); }, []); return (
Kevin's Ladder scaled entry · 6r
{rungs.map((r, i) => { const isFill = r.state === 'fill'; const isArm = r.state === 'arm'; const isActive = i === active; return (
{String(i + 1).padStart(2, '0')}
{r.px}
{r.d}
{r.state}
); })}
); } function StopLossGauge() { const [val, setVal] = useState(2.7); useEffect(() => { const id = setInterval(() => { setVal(v => { const next = v + (Math.random() - 0.5) * 0.6; return Math.min(4.9, Math.max(0.2, next)); }); }, 1100); return () => clearInterval(id); }, []); const pct = val / 5; return (
Stop-loss policy · unmonitored overnight σ
drawdown {val.toFixed(2)}% / threshold 5.00%
{/* threshold ticks */} {[1, 2, 3, 4].map(t => (
))}
0%1%2%3%4%5% kill
); } /* ───── SENTINEL PRO CARD ───── */ function SentinelProCard() { return (
{/* header */}
◆ Card 02 · Predictive Simulation
SLATE · LIVE

Sentinel Pro Engines

Predictive Python-based simulation models for NHL, NFL, MLB, and NBA. Executes massive 10,000-iteration Monte Carlo environments. Actively scrubs live rosters to recalculate TS% and usage voids, outputting Log5 cross-slate discrepancy matrices for mathematically validated +EV targets.

); } function LeagueRow() { const leagues = [ { k: 'NHL', state: 'SETTLED', tone: 'mute' }, { k: 'NBA', state: 'LIVE', tone: 'cyan' }, { k: 'NFL', state: 'PRE-LOCK',tone: 'purple' }, { k: 'MLB', state: 'IDLE', tone: 'mute' }, ]; return (
{leagues.map(l => (
{l.k}
{l.state}
))}
); } function PythonSnippet() { const lines = [ { n: 1, s: '#', t: ' simulate.py · sentinel-pro v3.1' }, { n: 2, s: 'from', t: ' sentinel.engine import MonteCarlo, Slate' }, { n: 3, s: 'from', t: ' sentinel.risk import Policy' }, { n: 4, s: '', t: '' }, { n: 5, s: 'slate', t: ' = Slate.from_live("NBA-2025-03-14")' }, { n: 6, s: 'slate', t: '.scrub(injuries=True, recompute=["TS%", "USG"])' }, { n: 7, s: '', t: '' }, { n: 8, s: 'mc', t: ' = MonteCarlo(iterations=10_000, seed="hkc")' }, { n: 9, s: 'mc', t: '.policy = Policy(stop_loss=0.05, dynamic=True)' }, { n: 10, s: 'results', t: ' = mc.run(slate, output="log5_matrix")' }, { n: 11, s: '', t: '' }, { n: 12, s: 'print', t: '(results.cross_slate_ev(min_conviction=0.62))' }, ]; return (
simulate.py
python · 3.12 
        {lines.map((l, i) => (
          

            {l.n}
            
              {l.s.startsWith('#') ? (
                {l.s + l.t}
              ) : (
                <>
                  
                  {
                    l.t
                      .replace(/("[^"]*")/g, '\x01$1\x01')
                      .split('\x01')
                      .map((seg, j) => seg.startsWith('"')
                        ? {seg}
                        : {seg}
                      )
                  }
                
              )}
            
          

        ))}
        

          13
          {'>>> '}
          stop_loss policy armed · 5.00% dynamic · 10,000 iterations dispatched
          ▍
); } function PyTok({ s }) { if (!s) return null; const kw = ['from','import','print','def','return','if','else','for','in','as']; const isKw = kw.includes(s); if (isKw) return {s}; if (/^[A-Z]/.test(s)) return {s}; return {s}; } function MonteCarloCounter() { const [n, setN] = useState(0); const target = 10000; useEffect(() => { if (n >= target) { const r = setTimeout(() => setN(0), 1400); return () => clearTimeout(r); } const step = Math.max(57, Math.floor((target - n) / 22)); const id = setTimeout(() => setN(v => Math.min(target, v + step)), 38); return () => clearTimeout(id); }, [n]); const pct = n / target; return (
Monte Carlo run · NBA slate
{n >= target ? COMPLETE : 'EXECUTING…'}
{n.toLocaleString()} / 10,000 iter
); } function Log5Matrix() { // small 5x5 cross-slate discrepancy matrix const teams = ['LAL','BOS','DEN','PHI','MIA']; const grid = useMemo(() => { return teams.map((_, r) => teams.map((__, c) => { if (r === c) return null; const v = ((Math.sin(r * 7.1 + c * 3.7) + Math.cos((r + c) * 1.9)) * 0.28) + 0.5; return v; }) ); }, []); const cell = (v) => { if (v === null) return { bg: 'rgba(255,255,255,0.02)', text: '#363941', val: '—' }; if (v > 0.62) return { bg: 'rgba(134,239,172,0.18)', text: '#86efac', val: v.toFixed(2) }; if (v > 0.55) return { bg: 'rgba(196,181,253,0.14)', text: '#c4b5fd', val: v.toFixed(2) }; if (v < 0.40) return { bg: 'rgba(244,114,182,0.10)', text: '#f9a8d4', val: v.toFixed(2) }; return { bg: 'rgba(255,255,255,0.03)', text: '#8a8d96', val: v.toFixed(2) }; }; return (
Log5 · cross-slate discrepancy +EV ≥ 0.62
{teams.map(t =>
{t}
)} {grid.map((row, ri) => (
{teams[ri]}
{row.map((v, ci) => { const c = cell(v); return (
{c.val}
); })} ))}
); } /* ────────────────────────────────────────────────────────────────────────── */ /* CORE TECH */ /* ────────────────────────────────────────────────────────────────────────── */ function CoreTech() { return (
{/* body copy left */}

Identifying mathematical anomalies (+EV) requires heavy, near-instantaneous reasoning over dense statistical matrices.

Sentinel architecture relies on industry-leading LLM reasoning to ingest raw simulation CSVs, live injury reports, and complex blockchain logs simultaneously.

By acting as our core cognitive engine, it synthesizes dense mathematical context without hallucination to output verified, high-conviction logic structures for automated execution.

{/* small spec table */}
{[ ['Reasoning model', 'Anthropic · extended thinking'], ['Context window', '200k tokens · streaming'], ['Ingestion plane', 'CSV · JSONL · Parquet · WS'], ['Verification', 'Structured-output + cross-check'], ['Determinism', 'Seed-pinned · log5-anchored'], ].map(([k, v]) => (
{k}
{v}
))}
{/* reasoning trace right */}
); } function ReasoningTrace() { const [phase, setPhase] = useState(0); useEffect(() => { const id = setInterval(() => setPhase(p => (p + 1) % 4), 1700); return () => clearInterval(id); }, []); const inputs = [ { label: 'simulation_run.csv', meta: '10,000 × 47 cols', icon: 'csv', lines: [ 'iter,player,proj_pts,proj_ts,usg_void,…', '0001,L.James,28.4,0.612,0.04,…', '0002,L.James,27.8,0.609,0.04,…', '0003,L.James,29.1,0.617,0.05,…', '…', ], }, { label: 'injury_feed.jsonl', meta: 'streaming', icon: 'json', lines: [ '{"team":"LAL","plyr":"AD","status":"OUT"}', '{"team":"BOS","plyr":"JT","status":"GTD"}', '{"team":"DEN","plyr":"NJ","status":"ACTIVE"}', '…', ], }, { label: 'helius_logs.ws', meta: 'mainnet-beta', icon: 'chain', lines: [ 'slot 285341022 swap +12,400 SOL → BONK', 'slot 285341023 liq+ WIF/SOL $1.84M', 'slot 285341025 burn 4,800 SOL', '…', ], }, ]; return (
Reasoning trace · trace-id 0x9c…41af
streaming
{/* 3 input panels */}
{inputs.map((inp, i) => (
{inp.label}
{inp.meta}
= i ? 'bg-glowc' : 'bg-white/15') }/>
{inp.lines.map((l, j) => (
{l}
))}
))}
{/* converge arrows */}
{[100, 300, 500].map((x, i) => ( i ? '#c4b5fd' : 'rgba(255,255,255,0.12)'} strokeWidth="1" fill="none" strokeDasharray="2 3" /> ))}
{/* reasoning core */}
◆ Cognitive synthesis · extended thinking
Δ 1.84s
[001] ingesting 3 sources · 240k tokens · pinned seed
[002] reconciling injury_feed → recomputing TS% · USG voids for 4 rotations
[003] projecting Log5 cross-slate discrepancy against MC output (10,000 iter)
[004] verifying conviction ≥ 0.62 · checking against blockchain liquidity drift
→ emit 3 high-conviction +EV targets; arm Kevin's Ladder · σ=5.00% ▍
{/* output chips */}
{[ ['NBA · LAL/DEN o225.5', '0.71'], ['SOL/BONK pool entry', '0.68'], ['NBA · BOS −4.5 1H', '0.64'], ].map(([k, c]) => (
Target
{k}
Conv.
{c}
))}
); } function FileIcon({ kind }) { if (kind === 'csv') { return ( ); } if (kind === 'json') { return ( ); } return ( ); } /* ────────────────────────────────────────────────────────────────────────── */ /* FOOTER */ /* ────────────────────────────────────────────────────────────────────────── */ function Footer() { return ( ); } /* ────────────────────────────────────────────────────────────────────────── */ ReactDOM.createRoot(document.getElementById('root')).render();