CrownThrive • CHLOM™ Confidential Algorithm & Ops Playbook V1.1

Classification: CrownThrive Internal • Trade Secret • Attorney–Client Draft

Scope: End‑to‑end algorithms, scoring formulas, model specs, data schemas, rule DSL, engine logic, proofs/invariants, and implementation guides for all core subsystems powering CHLOM™, LEX, DLA, TLaaS, ADE, ACE, CrownLytics, CrownPulse, FindCliques / NFTCliques / ChainCliques, ThriveSeat, AdLuxe Network, CrownRewards, CrownFluence, Kamora360, NeuralCraft AI Studio, and related services.


Use this document to (a) generate provisional applications; (b) brief counsel; (c) guide engineering builds. Keep off public networks.

0) Architecture at a Glance

  • Layer‑1 Metaprotocol: Compliance‑at‑Consensus; custom VM (ComplianceVM), State (License Registry + Audit Log), Privacy (ZK), Execution (Rule DSL).
  • Control Plane: TLaaS, LEX, DLA, ADE, ACE, Oracles & Governance Scribes (OGS).
  • Data Plane: Transaction Graph, Identity Graph, License State Machine, Payout Graph.
  • AI Plane: Risk Scoring, Fraud/Anomaly Detection, Reputation & Sentiment (CrownPulse), Matching (Cliques), Forecasting (AdLuxe & CrownLytics).

Key invariants (must always hold):

  • I1 Compliance Finality: A block is final only if every included transaction passes
  • I2 Value Conservation: ∑Inputs = ∑Outputs + Fees + Taxes + Insurance + (Escrow Δ) for each settlement window.
  • I3 License Liveness: Every active license NFT is either VALID, SUSPENDED, or REVOKED and transitions via authenticated events only.
  • I4 Privacy Soundness: Any private predicate used in consensus has a valid ZK proof verified by on‑chain verifier.

1) Rule DSL (Metaprotocol) — ACE/ComplianceVM

Goal: Convert regulations into executable logic.

1.1 Grammar (EBNF)

POLICY      := 'policy' IDENT '{' RULE+ '}'
RULE        := 'require' PREDICATE ('else' ACTION)? ';'
PREDICATE   := COMPARISON | LOGIC
COMPARISON  := FIELD OP VALUE | FUNC '(' ARGS ')' OP VALUE
LOGIC       := PREDICATE (('and'|'or') PREDICATE)+ | 'not' PREDICATE
OP          := '==' | '!=' | '<' | '<=' | '>' | '>=' | 'in' | 'subset'
ACTION      := 'deny' | 'suspend' | 'route_tax' '(' JURIS ',' RATE ')' | 'notify' '(' ROLE ')'
FIELD       := IDENT ('.' IDENT)*

1.2 Example — Export Control

policy EAR_742 {
  require exporter.kyc.level >= 2;
  require not buyer.country in {"IR","KP","SY"} else deny;
  require item.eccn in whitelist else suspend;
  require tx.value_usd <= limits.by_country(buyer.country);
  require zkp_attest("sanctions_clean") == true;
}

1.3 Execution Semantics

  • Parse → build AST → compile to ComplianceVM bytecode.
  • Deterministic evaluation across validators (pure functions + provided oracle snapshots).
  • Side effects limited to

2) Identity & Privacy — ZK + Fingerprint‑Backed DID

2.1 Data Model

  • DID
  • BioHash v2
  • Selective Disclosure

2.2 ZK Circuits (high‑level)

  • Proof A — BioMatch: Prove
  • Proof B — SanctionsClean: Merkle‑membership proof over compliance dataset snapshot.
  • Proof C — LicenseTier: Prove possession of credential with tier ≥ required threshold.

2.3 Identity FSM

NEW → VERIFIED → (VALID | SUSPENDED | REVOKED)
Transitions gated by ZK proofs + DLA authority signature.

2.4 Implementation (pseudocode)

# zk_prove_biomatch(fp_template, biohash, salt): returns proof π
# on-chain verifier verifies vk, π against public inputs

def pre_trade_check(tx):
    assert verify_zk(tx.zk_biomatch)
    assert verify_zk(tx.zk_sanctions)
    assert verify_cred(tx.cred_vc, schema="KYC_TIER")
    run_policy(tx, compiled_policy)
    return True

3) Risk & Compliance Scoring — AI/ML Stack

3.1 Features (canonical)

  • KYC/Behavioral: account_age, doc_consistency_score, device_entropy, velocity.
  • Graph: pagerank(entity), betweenness(tx_graph), community_overlap(sanction_clusters).
  • Transaction: amount_z, geo_distance, time_of_day, method, merchant_mcc.
  • Text/Semantic: invoice_ocr_similarity, purpose_embedding_distance.

3.2 Models

  • Compliance Risk Score (CRS): Logistic regression with monotonic constraints for auditability.
    • Calibration via isotonic regression; bins 0‑1.
  • Anomaly Detection: Robust autoencoder + Isolation Forest ensemble; voting threshold τ.
  • Fraud Graph: Heterogeneous GNN (HAN) over Entity–Wallet–Device–IP graph; edges typed.
  • Document Integrity: Vision Transformer fine‑tuned for tamper cues; output

3.3 Decision Layer

if S_CRS ≥ 0.85 or anomaly_vote≥2: deny
elif 0.65 ≤ S_CRS < 0.85: hold + ZK reverify + human review SLA=2h
else: allow

3.4 Drift & Governance

  • PSI > 0.25 or AUC drop > 5% triggers retrain proposal → DLA vote.
  • All models signed and registered in Model Registry on-chain (hash + license).

3.5 Training Data Schema (sanitized)

entities(entity_id, did, kyc_tier, risk_segment, created_at)
transactions(tx_id, entity_id, amount, currency, geo, mcc, method, ts, label)
artifacts(tx_id, doc_hash, ocr_text, doc_score)
graph_edges(src_id, dst_id, edge_type, weight, ts)
labels(tx_id, y_fraud, y_violation)

3.6 Evaluation

  • Metrics: AUC, PR‑AUC, Recall@FPR=1%, Detected$ per 1k tx, Avg Review Time.
  • Fairness: ΔFPR across segments ≤ 2%.

4) ADE — Automated Distribution Engine (Royalties/Tax/Insurance/Escrow)

4.1 Payout Graph

  • DAG

4.2 Settlement Formula


P_i(t) = \min\{ cap_i(t), \max\{ floor_i(t), s_i \cdot (A - T - F - E) + adj_i(t) \} \}
  • Rounding: Bankers rounding; dust → community pool; determinism ensured by fixed order.

4.3 Tax Routing

T = Σ_j amount * tax_rate(jurisdiction_j, mcc, nexus)
route(T, authority_wallet)

4.4 Yield Allocation (DeFi)

  • Risk‑budget optimizer with constraints
  • Greedy knapsack by Sharpe proxy when latency‑constrained.

4.5 Smart Contract Skeleton (Solidity‑like)

struct Split {address to; uint32 bps; uint128 cap; uint128 floor;}
function settle(bytes32 txid, Split[] memory s) external verifies(txid) {
  uint256 A = getGross(txid);
  uint256 T = computeTax(txid);
  uint256 base = A - T - fee(txid) - escrow(txid);
  for (Split memory sp: s) {
    uint256 amt = clamp(base * sp.bps / 10000, sp.floor, sp.cap);
    pay(sp.to, amt);
  }
  routeTax(T); emit Settled(txid);
}

5) LEX — License Exchange (Compliance‑Before‑Trade)

5.1 Pre‑Trade Algorithm

def can_trade(a, b, asset):
    assert has_valid_license(a, asset)
    assert has_valid_license(b, asset)
    assert run_policy(asset.policy, a, b)
    assert price_oracle_sane(asset)
    return True

5.2 Order Matching with Compliance Hooks

  • Orders enter book only if
  • On match,

5.3 Dispute & Rollback

  • Challenge window

6) DLA — Decentralized Licensing Authority (Dual DAO)

6.1 Voting

  • House‑I (Identity/Consumer): one‑person‑one‑vote via soulbound credential + Proof‑of‑Humanity.
  • House‑II (Regulators/Enterprise): stake‑weighted with quadratic cap; slashing for malicious proposals.
  • Proposal passes if:

6.2 Governance Scribe

  • Append‑only log:

7) Oracles & Scribes (OGS)

7.1 Data Integrity

  • Aggregator: median‑of‑n with trimmed 20%; fault tolerance f = ⌊(n−1)/2⌋.
  • Attestation: Ed25519 signatures; feed IDs; slash misreporters by bonded stake.

7.2 Snapshotting

  • Each policy references oracle snapshot

8) CrownLytics — Analytics & Forecasting

8.1 Heatmaps & Conversion Lift

  • Bayesian hierarchical model for multi‑property CTR; partial pooling per property, device, segment.
  • Uplift modeling using causal forests for treatment (placement A/B).

8.2 Metrics

  • Session‑to‑Book (ThriveSeat), View‑to‑Claim (Locticians), Add‑to‑Cart (XENthrive), Ad Spend ROAS (AdLuxe).

9) CrownPulse — Sentiment & Reputation Index

9.1 Signals

  • Text embeddings (domain‑specific), review star trend, dispute rate, refund rate, moderation flags, network centrality.

9.2 Score


S_{Pulse} = w_1 z(emb\_sent) + w_2 z(Δstars) + w_3 z(1-complaint\_rate) + w_4 z(pagerank)

10) Cliques Matching (FindCliques / NFTCliques / ChainCliques)

10.1 Objective

  • Maximize mutual‑fit score across purpose, expertise, chain affinity, engagement time, and trust signals.

10.2 Algorithm

  • Two‑tower embedding model + cross‑attention reranker.
  • Constraint solver to enforce group diversity, time zone coverage, and minimum trust score.

10.3 Score


S_{match} = α\langle u, g \rangle + β\,trust(u) + γ\,compat(u,g) - δ\,overlap(u,g)

11) AdLuxe Network — Bidding & Placement

11.1 Ranking

  • eRPM =
  • Pacing controller: PID loop to respect daily budgets.

11.2 Creative QC

  • Vision/text classifiers for policy violations; OCR rule checks; SHA‑256 dedupe.

12) CrownRewards — Loyalty & Redemption

12.1 Points Engine

  • Earn rules via DSL subset: event→points; caps, tiers, decay.
  • Redemption smart contract with dynamic exchange rate tied to treasury solvency.

12.2 Anti‑Abuse

  • Device entropy + graph link score; cooldowns; negative points for abuse signals.

13) ThriveSeat — Booking & Payments (Stripe Connect Express Ready)

13.1 Availability Engine

  • Interval Tree per provider; O( log n ) insert/lookup; atomic reservation with conditional hold TTL.

13.2 Pricing

  • Piecewise functions by service + duration + add‑ons; coupon stack validator; tax nexus via ACE.

14) NeuralCraft AI Studio — Usage‑Metered AI

14.1 Quotas & Billing

  • Token metering per session; tiered price curves; affiliate splits via ADE.

14.2 Model Ops

  • Prompt registry (hash‑addressed); safety filters; audit trail of outputs (hash only, encrypted blob off‑chain).

15) Data Governance, Security & Privacy

  • Encryption: PII at rest (AES‑GCM); keys via HSM; envelope encryption.
  • Access: ABAC tied to DLA credentials; just‑in‑time grants; dual control for exports.
  • Privacy Enhancements: DP training for select models (ε ≤ 4); K‑anonymity for analytics release.

16) Deployment Topology

  • Validators: geographically distributed; TEEs optional for private mempool.
  • Indexers: read‑only replicas feeding CrownLytics.
  • Bridges: light‑client based, message passing with fraud proofs.

17) APIs (Selected)

POST /v1/policy/compile        → {bytecode}
POST /v1/identity/prove        → {proof}
POST /v1/trade/precheck        → {ok, reason}
POST /v1/settlement/execute    → {tx_hash}
GET  /v1/model/registry/:id    → {hash, version, metrics}

18) TLA+ Invariants (sketch)

Invariant ValueConserved == \A tx \in Settlements: SumIn[tx] = SumOut[tx] + Taxes[tx] + Fees[tx] + EscrowDelta[tx]
Invariant LicenseStates   == LicenseState \in {VALID, SUSPENDED, REVOKED}
Invariant ZKSoundness     == \A p \in ZKProofs: Verified(p)

19) Implementation Guides (per subsystem)

19.1 ACE / Rule DSL

  • Stack: Rust compiler → WASM → ComplianceVM bytecode.
  • Milestones: Grammar parser → bytecode gen → on‑chain verifier tests → 50 canonical policies.

19.2 ADE

  • Stack: Solidity/Vyper contracts; TypeScript SDK; graph payouts.
  • Tests: Property‑based tests for rounding, caps/floors, vesting; fuzz tax tables.

19.3 LEX/DLA

  • Stack: Matching engine in Rust; governance on-chain modules; event sourcing.
  • SLA: Match latency < 50ms p95; dispute resolution < 24h.

19.4 AI Models

  • Stack: PyTorch/Lightning; Feast feature store; MLflow registry; Kubeflow pipelines.
  • Ops: Canary model rollout; shadow eval; backtest harness.

20) Datasets (internal)

  • KYC Artifacts: hash pointers only; stored in secure vault.
  • Sanctions & Watchlists: periodic snapshots; Merkle roots published by Scribes.
  • Behavioral Logs: clickstream, booking, ad events; aggregated to protect privacy.

Note: This section documents schema, not raw PII.

21) Compliance & Legal Notes

  • Map each model/engine to provisional filing(s) and white/black/gold paper references.
  • Attach figure set: Architecture, Transaction Lifecycle, TLaaS/LEX/DLA flows, ADE map, Privacy/DAO, Metaprotocol stack.

22) Test Vectors (samples)

{
  "tx": {
    "amount": 1500.00,
    "currency": "USD",
    "mcc": "5812",
    "buyer_country": "US",
    "zk": {"biomatch": "0xabc...", "sanctions": "0xdef..."}
  },
  "policy": "policy SALES_US { require tx.amount <= 2000; require zkp_attest(\"sanctions_clean\"); }"
}

23) Rollout Plan (90‑Day)

  • Days 0‑30: ACE compiler, ComplianceVM MVP, ADE v0, Identity ZK circuit stubs.
  • Days 31‑60: LEX pre‑trade hooks, Model Registry, Risk score v1, Oracles.
  • Days 61‑90: DLA governance alpha, Full ZK verifier, Yield router, Bridges PoC.

24) What to File (Provisional Index)

  1. CHLOM Layer‑1 Metaprotocol & ComplianceVM
  2. TLaaS tokenized licensing, License Registry FSM
  3. LEX compliance‑before‑trade, atomic ADE settlement
  4. DLA dual‑house governance + Governance Scribe
  5. ADE payout graph + tax/yield optimizer
  6. Identity ZK proofs + BioHash + selective disclosure
  7. Risk/Anomaly/Fraud ML stack & governance triggers
  8. Oracles & Scribes aggregation + slashing
  9. CrownLytics uplift modeling; CrownPulse reputation index
  10. Cliques matching two‑tower + constraints

Appendix A — Mathematical Details

  • Isotonic Calibration: piecewise constant mapping optimizing mean squared error of probabilities.
  • Sharpe Proxy: with robust estimators (Huber).
  • Graph Regularization: .

Appendix B — Security Proof Sketches

  • Oracle Safety: With ≥ 2f+1 honest feeds, trimmed mean resists ≤ f Byzantine reporters.
  • Value Conservation: ADE settlement is a pure function of inputs; unit tests + formal spec ensure equality.

Appendix C — Data Protection Patterns

  • Data minimization; purpose binding; encrypted learning with DP for high‑risk cohorts.

Appendix D — API/ABI Tables

  • Function selectors, event topics, role requirements.

End of Document

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CrownThrive • CHLOM™ Confidential Algorithm & Ops Playbook V1.0
CrownThrive • CHLOM™ Confidential Algorithm & Ops Playbook V1.3 (Extended)