Scientific Analytics Alliance · Sovereign Risk Infrastructure
The SAA Sovereign Risk Infrastructure.
A class-routed deterministic acceleration layer for institutional risk math, exposed as seven production modules behind private endpoints, with a 22-agent governance and audit council layered on top — math first, agents second. Enterprise Wave canonical pack (v2, MC-challenger-anchored) — 8,800 cases per backend (GPU grid + CPU mirror) · 8.8 B paths per backend · CVaR 99.9 within 0.035% of 10 M MC · 0 execution failures. Trading-desk surfaces: tick replay p99 0.497 ms over 24 M updates; pre-trade mixed gate p99 0.920 ms over 24 M orders (canonical clean rerun). Built for banks, insurers, asset managers, sovereign treasuries and regulators that require transparent, auditable, sub-second analytics with institutional-grade fault tolerance — not a replacement for incumbent risk platforms (Aladdin, Bloomberg, Murex, MSCI), but an embedded layer that accelerates validated stress paths and routes regime-shift cases to fallback or review.
ARIN22 is a US-registered name for the deterministic risk-core. No GPU lock-in for correctness — kernel correctness validates on commodity ARM CPU at ~99 µs single kernel call, holding the same envelope from D = 4 synthetic baseline through D = 200 on real portfolios — no degradation, orders of magnitude faster than a matched-accuracy Monte-Carlo equivalent, with better than 0.05% deviation at the 99.9th percentile vs MC gold-standard. The 8×H100 NVIDIA Innovation Lab stack is layered on top as a separate lane for batch throughput at Enterprise-Wave scale — scale, not correctness; the two lanes are never collapsed into a single “kernel latency” number. Every result stamped with hardware fingerprint and run SHA for replay. Detailed benchmark numerics (per-run latency, speedup multiplier, mean-diff vs MC reference) released to bank model-risk under NDA only.
Status
Pre-client institutional diligence-ready
Run 12 closed (commit 3717fc4d) · Rev 2026-05-23 · Enterprise Wave v2 canonical · 8 / 8 H100 utilised · 0 scenario failures · sampler-invariant routing (commit d18a4af6)
S2 · Canonical metrics
System spec · institutional-grade · pre-client diligence-ready.
Public tier-1 surface only. Detailed numerics (per-run latency, speedup multiplier, mean-diff) are NDA-disclosed to bank model-risk reviewers. CPU correctness (~99 µs single kernel call · constant from D = 4 synthetic to D = 200 real portfolios · no degradation) and GPU batch lane are explicitly separated as different metrics — not collapsed into one “kernel latency” number.
Lane discipline. Kernel correctness is CPU-bound and substrate-portable (~99 µs single kernel call on commodity ARM, no GPU required). Kernel batch throughput is the 8×H100 NVIDIA Innovation Lab lane (sub-ms per-run math path at Enterprise-Wave scale). The two are different metrics, never collapsed.
S3 · Validation evidence · v2 canonical · commit 3717fc4d
Enterprise Wave v2 · MC-challenger-anchored.
Pre-client institutional validation surface — v2 canonical, MC-challenger-anchored at the 99.9 tail. Reproducibility, cross-platform parity, deep-tail accuracy, desk-risk replay, pre-trade decision triage, calibration discipline, sampler-invariant routing. Every figure below is hash-chained, reproducible, with disclosed bands. The v1 8-Wave aggregate (~1.12 M lineage cases / 1.06 T paths) is preserved on the data-room page for substrate breadth — superseded as headline by v2 canonical, kept as lineage. Realised regulatory backtesting harness is BACKTEST_HARNESS_ARMED; REALIZED_BACKTEST_PASS is forbidden before 250 matched observations — a gate, not a marketing claim.
1,000 repeat runs across 8/8 GPUs — same input collapses to 1 unique normalised metric hash. Batch-order invariance: PASS. Fresh-process invariance: PASS. Sampler-invariant routing & policy across a 5,040-surface PRNG / Sobol / LHS campaign — 0 tail-route / 0 policy-bucket changes; numeric drift bounded p95 1.88% (commit d18a4af6). Determinism is not a feature flag; it is the substrate.
Enterprise Wave canonical surface, MC-challenger-anchored at the 99.9 tail (10 M MC reference). CVaR 99.9 within 0.035% of 10 M MC across the 8,800-case canonical grid. CRN 99.9 GPU↔CPU parity audited on the worst-tail sub-sample of 100 cases (part of the 8,800, not independent). Detailed numerics published to bank model-risk under NDA.
Run 11 calibration: worst 360D CVaR 99.9 corrected from 92.46% NAV → 73.39% NAV. Run 12 post-calibration MC audit (20 worst cases × 4 seeds × 10 M paths): CVaR 99.9 max abs 0.2822%. Found → fixed → audited — the calibration loop is documented, not hidden.
S4 · Architectural foundation · two-tier stack
KOKON sovereign control plane. ARIN22 mathematical kernel.
Two foundational tiers orchestrate the seven production modules below. KOKON additionally exposes its own operator endpoint (Module 07).
KOKON — Sovereign Control Plane
The standalone control plane orchestrating governance, AI-agent calibration, voice intelligence, council sessions, and a continuous closed-loop (OODA, Boyd 1976) decision cycle with NVIDIA-first AI routing. Event backbone with HMAC-signed webhook delivery, opportunity pipeline, approval workflows, and multi-project rollout. Closed-loop agent architecture: Entity Memory → RAG Knowledge Corpus → Agent Assessment → Outcome Feedback → calibration-aware weight recalibration. Webhook-isolated, zero-trust topology across all production modules.
ARIN22 — Mathematical Kernel
The proprietary deterministic computational core for systemic risk. Replaces brute-force Monte Carlo path enumeration with a protected mathematical kernel — sub-millisecond per-run math path on the 8×H100 lane, orders of magnitude faster than classical MC at matched accuracy (better than 0.05% deviation at the 99.9th percentile vs MC gold standard). Kernel correctness validates on commodity ARM CPU at ~99 µs single kernel call, holding constant from D = 4 synthetic to D = 200 on real portfolios — no degradation — substrate-portable, no GPU lock-in for correctness; H100 lane is for batch throughput, not correctness. Powers the 22-agent ARIN council and every module that needs sub-second risk revaluation. Designed for Fed/OCC/FDIC SR 26-2 model risk management with deterministic reproducibility and policy gates. Internal kernel construction is a trade secret of Scientific Analytics Alliance Inc. Detailed benchmark numerics released to bank model-risk under NDA only.
S5 · Hallucination prevention funnel
Three structural mechanisms separate ARIN from generic LLM stacks.
Deterministic constraint · outcome-locked learning · graceful degradation. None of the three depends on a prompt-engineering layer.
Each asset class activates only the relevant subset of the 22-agent council, eliminating token waste and the structural risk of cross-domain hallucination (e.g. a digital-asset analysis does not invoke physical-inventory agents). Conflict detection is scoped to adjacent risk domains, so disagreements that matter are surfaced and disagreements that do not are suppressed.
The learning layer refuses to recalibrate agent weights from internal confidence alone. Weights change only after a realised outcome is observed and scored, which prevents the self-reinforcing inflation loop that destabilises generic LLM agent stacks.
LLM timeouts and rate-limit errors degrade gracefully — the orchestrator computes a partial consensus from the available agents and flags the verdict for human review. Every verdict carries a cryptographic audit trail aligned with Fed/OCC/FDIC SR 26-2 model risk governance and EU AI Act Article 12 record-keeping.
S6 · Production modules · private endpoints · ARIN22-powered
Seven customer-facing modules. One kernel.
Each module is exposed through a private endpoint under NDA, all powered by the ARIN22 kernel where sub-second risk math is required and orchestrated by the KOKON control plane. KOKON appears both as the orchestrator (see Architectural Foundation above) and as Module 07 — an operator-facing endpoint for governance, council sessions, and audit replay.
ARIN — 22-agent council Live
The 22-agent AI council with Meta-Decision Governor, Entity Memory, and Learning Agent. Agents operate as bounded microservices publishing typed event contracts on a durable message bus, with targeted verdict delivery and a separate global audit fan-out for full traceability. NIM API + NeMo Guardrails plus a graph-neural-network layer for systemic-risk propagation. Consensus combines confidence and historical reliability of each agent — not simple averaging; specific weighting scheme is internal.
Global Risk Intelligence Live
Physical Economy Operating System — the Physical-to-Financial Translation Engine. 3D Command Center, eight strategic analysis modules (Macro, Supply Chain, Financial, Cyber, Climate, Social Stability, Geopolitical, Infrastructure), zoned enterprise placement across 50+ cities, multi-domain Unified Stress Report. Real-time ingestion from authoritative public data sources (USGS, FEMA, WHO, World Bank, IMF, OFAC, CISA KEV). AI-Q conversational interface and System Overseer for anomaly detection.
News Analytics Portal Live
Narrative intelligence engine with 12 risk-specialised agents. RiskMirror for cross-source verification, Headline-to-PnL impact estimation, Impact Graph for contagion visualisation, Sentiment Timeline, ecosystem mapping, deep graph analytics. NVIDIA NIM for multilingual processing, NeMo Guardrails for narrative compliance. Sector exposure analysis and automated risk-narrative generation.
Risk Analyzer Live
Portfolio-level quantitative risk engine. VaR / CVaR computation, large-scale stress simulation with optional ARIN22 deterministic acceleration (sub-millisecond revaluation), multi-factor stress testing, factor decomposition, backtesting frameworks, portfolio optimisation. GPU-accelerated for institutional-grade throughput. AI Service layer with NVIDIA NIM inference and RAG for contextual analysis. Direct export to ARIN for verdict synthesis.
Investment Analytics Live
Equity and cross-asset research platform. Report Agent with institutional-grade V2 reports, watchlist management, proactive sector scanning, async report generation pipeline. Data ingestion from yfinance and SEC EDGAR. Factor decomposition, sector rotation analysis, performance attribution, valuation models. Direct ARIN integration for single-verdict synthesis on any public equity or ETF.
Digital Assets Analytics Live
Digital-assets risk and intelligence platform. Multi-dimensional metrics across six categories, proprietary rating system, Risk & Intelligence layer. On-chain analytics, DeFi protocol decomposition, large-holder flow intelligence, Report Orchestrator for structured output. Send-to-ARIN for cross-domain verdict. NVIDIA NIM inference for real-time narrative analysis. Domain-bounded routing ensures a crypto-specific agent graph — no physical-asset hallucination.
KOKON — Control Plane Live
Service 7 control plane — closed-loop (OODA, Boyd 1976) decision cycle, 22-agent council orchestration, voice intelligence, approval workflows, HMAC-signed event delivery. While KOKON is architecturally the cross-module orchestrator (see Architectural Foundation above), it also exposes an operator endpoint for governance dashboards, council sessions, calibration profiles, and audit replay. Bilingual EN / RU operator UI; human-in-the-loop approval gate for high-stakes verdicts; aligned with EU AI Act Article 12 record-keeping.
KOKON is the only module that appears twice on this page on purpose — once at the Foundation tier as the cross-module orchestrator, and again here as Module 07 with its own customer-facing operator endpoint. The other six modules publish typed event contracts to the durable message bus that KOKON arbitrates.
- Governance dashboards — tenant-wide policy, role binding, audit retention controls
- Council sessions — live 22-agent verdict review, dissent maps, Dual-Publish playback
- Audit replay — SHA-256 chained, 7-year retention, regulator walkthrough mode
- Calibration profiles — per-domain weight tuning, Zero-Outcome Freeze gate, outcome loop
- Approval workflows — human-in-the-loop gate for high-stakes verdicts (EU AI Act Art. 12)
- HMAC-signed event delivery — webhook fan-out to all six sister modules via durable bus
- Voice intelligence — bilingual EN / RU operator interface, council session transcription
S7 · Architecture · layered pipeline
Sensor nodes → event bus → AI orchestration → state stitching.
Network topology
Layer 1 — Sensor nodes
Bounded-context services (Equity Node, Digital Assets Node, etc.) collect data, compile structured payloads, persist to a local cache, package the payload into a typed event contract, and publish to the global event bus. A live socket channel is held open for the asynchronous verdict response.
Layer 2 — Event bus
Durable, persistent message bus with a single typed entry point, targeted reply channels for individual sensor nodes, and a separate global audit fan-out for downstream consumers. Specific broker, queue topology, and routing keys are operational detail and not disclosed publicly.
Layer 3 — AI orchestration
Asynchronous orchestration consumer with back-pressure and concurrency controls. Pulls reports, runs the 22-agent council with domain-bounded routing, computes a confidence-and-reliability-weighted consensus, and dual-publishes the verdict (author channel + audit log).
State machine & data flow
State stitching
When a sensor node receives a verdict, it locates the original report in its cache, attaches the council verdict with full audit trail, and transitions through its internal state machine to APPROVED or REVISION. A live UI event is pushed for instant feedback.
Data contracts
Typed schema contracts shared as an installable package enforce a unified ontology across all nodes. Schemas validate at serialisation boundaries — no unvalidated data crosses service boundaries.
Horizontal scalability
Stateless service architecture. Sensor and orchestration tiers scale independently behind the message bus, with automatic load-balancing across consumers. Each service is independently deployable and horizontally scalable.
S8 · Technology stack · NVIDIA-first
Compute · Data · AI.
Compute & Runtime
- Python and Go services with structured, streaming-capable APIs
- Asynchronous message bus with durable, persistent queues
- In-memory cache for low-latency state stitching
- Containerised deployment with full CI / CD
- Production observability and SRE tooling
Data & Storage
- Polyglot persistence: relational, time-series, graph, columnar, embedded
- Typed contract package shared across services
- Equity feeds (incl. SEC EDGAR) + multi-source government data
- On-chain and DeFi analytics integrations
- Specific vendor / engine choices are operational detail
AI & NVIDIA
- NVIDIA NIM API for production LLM inference
- NVIDIA NeMo Guardrails — safety & compliance
- Graph-Neural-Network layer for systemic-risk propagation
- GPU-accelerated quantitative compute layer
- Resilient retry / back-off logic for upstream rate limits
S9 · NVIDIA AI Enterprise stack
The full NVIDIA service-mesh view lives on a dedicated page.
NVIDIA Inception · Innovation Lab · 16 services live
See the full SAA × NVIDIA service-mesh integration map.
Sixteen NVIDIA services compose the integration surface across four categories — Core AI · Physical Simulators · Infrastructure · Data & Evaluation. Eleven are production-live; five are on the 2026 roadmap. The dedicated NVIDIA-stack page mirrors the same service-mesh view our internal SRE team monitors, with per-service status, hardware targets, the STAC-inspired compute-envelope evidence (14.875 s on 8×H100; archive SHA-256 b8193ba1…), and the Inception / Innovation Lab co-engineering inquiry.
S10 · Programs · Research · Technical materials
Affiliations · benchmarks · papers · DD package.
Institutional briefs · PDF
ARIN22 — Institutional FSI Brief
The deterministic-kernel evidence pack for banks, asset managers, insurers and sovereign desks — workloads, lanes, governance, posture.
Open the brief PDF · H100NVIDIA Innovation Lab — H100 Outcomes Brief
8×H100 validation outcomes from the NVIDIA Innovation Lab — canonical lanes, GPU/CPU parity, smoke-reproducible at hash level.
Open the briefBenchmarks, methodology papers, and architecture documentation for institutional due diligence and technical review.
SAA Alliance platforms provide research and analytics; they do not constitute individualised investment, legal, or tax advice. Past performance does not guarantee future results.
Math first · Agents second · Governor always · Audit forever