MawPulse Quantitative
Deterministic Models · Zero Hallucinations · Full Transparency
End-to-end autonomous quantitative analysis with
a strictly deterministic 12-engine architecture and bank-ready outputs.
Your data never touches a cloud server, an AI model, or a third-party API. Every engagement executes exclusively on an air-gapped local machine. When the engagement closes, your files are purged. We hold no copies, no logs, no backups.
Our MawPulse Agent processes your data using deterministic statistical and ML models (XGBoost, PCA, Monte Carlo, etc.) with no generative AI—every number comes with its exact source formula and full mathematical transparency.
Precision-engineered solutions for growing enterprises: automated financial reconciliation, bank-ready financial statements, and rigorous operational simulations to isolate and eliminate profit bleeds.
- Bank-Ready Results (Audit-Submit)
- Methodology Transparent (Validation)
- Air-Gapped Nodes (Isolated HW)
- Human Oversight (Optional Layer)
Institutional Capabilities
Select a division below to view analytical methodologies.
Advanced Quantitative
Institutional algorithmic modelling, market flow topology, and dimensionality reduction for hedge funds, VCs, and global supply chain operations.
- Predictive Classification Matrix (XGBoost)
- Regression & Dimensionality Reduction (PCA)
- Crypto Alpha Engine & Signals
Financial Solutions (SMB)
Audit-defensible, strictly deterministic accounting intelligence. We utilize Python arrays—never hallucinating LLMs—to construct mathematical proof for corporate finance.
- Bank-Ready Auditable Statements
- Monte Carlo Survival Forecasts
- Causal ROI Action Validation
Customer Analytics (SaaS)
Enterprise-grade predictive modeling for growth teams. Predict churn, optimize marketing ROI, and forecast customer lifetime value with absolute mathematical certainty.
- Customer Churn Prediction Engine
- Marketing Mix Modeling (MMM)
- Customer Lifetime Value (CLV) Forecast
Sample Reports
We don't just claim our models work — we prove it. Every report below was generated by our live engine on real, publicly available datasets. Click Preview to inspect any PDF inline.
Market Intelligence
Apple (AAPL), S&P 500, and Bitcoin across the full 2022–2024 market cycle.
Exploratory Data Audit
BTC shows 4.2x volatility vs AAPL · 3 structural breaks identified
Driver Analysis (Regression/PCA)
SPY explains 71% of AAPL variance (R²=0.71)
Illustrative example on limited data
Causal ROI (SCM)
Fed rate hike shows 14-day lagged BTC causal impact · E-value: 3.2
We report E-values and confidence intervals — no black boxes
Scenario Risk (Monte Carlo)
P90: +29.5% · P10 stress: -18.2% · VaR 95%: -21.4%
Fat-tail distributions capture Black Swan scenarios
SMB Retail Operations
20-SKU e-commerce ledger across 4 sales channels over a 2-year simulated period.
Exploratory Data Audit
Wholesale = 23% higher margin · 4 outlier SKUs flagged
Customer Segmentation (GMM)
Top 18% of orders drives 52% of total revenue
Probabilistic personas, not hard K-means boundaries
Financial Reconciliation
Gross margin: 38.4% · SBA Readiness: 74/100
Margin Protection Bundle
3 bleed SKUs isolated · Budget adherence: 71%
Three audits in one: Inventory + Budget + Expense
Credit Risk Assessment
German Credit benchmark dataset — globally used in academic & institutional risk research.
Exploratory Data Audit
Risk 70/30 imbalance · Age 25-35 = highest default rate (34%)
Driver Analysis (Regression/PCA)
Loan amount + duration explain 68% of risk variance
Example with no linear signal · Notice how we identify the top drivers of variance
Risk Classification + Survival
XGBoost AUC: 0.83 · Recall on high-risk: 79%
Causal ROI (SCM)
Credit history CATE: +0.31 (strongest default causal driver)
We report E-values and confidence intervals — no black boxes
Crypto Alpha Engine
BTC + ETH across the full 2022 crash (-77%), 2023 accumulation, and 2024 bull cycle.
Practice Gamma: Customer Analytics
Enterprise SaaS tracking model utilizing XGBoost survival curves, Bayesian attribution, and probabilistic cohorts.
Customer Churn Prediction Engine
Identified high-risk cohorts with 92% retention targeting accuracy
Key Drivers and Survival Waterfall pushed to executive summary
Marketing Mix Modeling (MMM)
Facebook Ads identified as peak driver; 15% budget reallocation recommended
Marginal ROI calculated via Bayesian Ridge + PCA synergy
Customer Lifetime Value (CLV)
High-LTV Whales segment configured 82% of future aggregate revenue
GMM probabilistic personas mapping negative-LTV limits
18 sample PDFs · Built on real public data · 27/27 math checks pass · Engine certified
Run on Your DataMarket Intelligence Terminal
Live signals — autonomous, zero user dependency
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Adjust your operational metrics to visualize the annual value of institutional-grade data architecture.
Secure sessions available for data audit and structural implementation.