The Quadrazene Framework
Four bonded Engines. One aromatic ring.
Insights knows, Governance protects, Advisory guides, Actions does. Each Engine's output becomes another Engine's input. Below: what each one does, with a real sample pulled straight from the app database.
Your AI that knows.
Ask anything about your business in plain English. Get cited, verified answers with charts and narrative, in seconds, not sprints.
No SQL. No dashboard sprawl. The Insights Engine mines historical patterns from every data source you have and returns grounded answers your team can defend.
Natural-language queries
Ask complex analytical questions the way you'd ask a senior analyst. No schema knowledge required.
Grounded + cited
Every number, entity, and claim traces back to its source. Verifiers block hallucinations before they reach you.
Automatic visualization
The right chart type for the result shape. Switch axes, filters, and comparisons interactively.
Narrative explanation
Every answer comes with a plain-English “why”. The drivers behind the trend, not just the trend.
Live sample · real data from the app database
Which product categories contributed most to the highest revenue months?
Electronics dominates the highest revenue months with consistent leadership across all three peak periods (March, July, October 2024), generating 37-39% of total revenue in each month. The category mix remains remarkably stable across these peak months, with Electronics, Home & Kitchen, and Accessories forming the top tier while Furniture consistently trails at roughly half the revenue of the leading category.
- Electronics leads all three highest revenue months with $1.45M (March), $1.34M (October), and $1.23M (July), showing consistent dominance despite month-to-month fluctuations.
- The revenue hierarchy remains locked across all peak months: Electronics > Home & Kitchen/Accessories (alternating 2nd/3rd) > Furniture, suggesting structural market positioning rather than seasonal shifts.
- Furniture consistently generates the lowest revenue at roughly $500-600K per peak month, representing only 40-42% of Electronics' revenue in the same periods.
- Home & Kitchen shows the most volatility among top categories, ranging from $872K (March) to $1.08M (July), a 23% swing that exceeds other categories' fluctuations.
▸ Inspect rows (12)
| category | revenue month | category revenue |
|---|---|---|
| Electronics | 2024-10 | $1.34M |
| Home & Kitchen | 2024-10 | $971K |
| Accessories | 2024-10 | $858K |
| Furniture | 2024-10 | $608K |
| Electronics | 2024-07 | $1.23M |
| Home & Kitchen | 2024-07 | $1.08M |
| Accessories | 2024-07 | $884K |
| Furniture | 2024-07 | $569K |
| Electronics | 2024-03 | $1.45M |
| Accessories | 2024-03 | $929K |
▸ Inspect SQL · executed against the configured System
SELECT
p.category,
DATE_FORMAT(o.order_date, '%Y-%m') AS revenue_month,
SUM(oi.quantity * oi.price_at_purchase) AS category_revenue
FROM orders o
JOIN order_items oi ON o.order_id = oi.order_id
JOIN products p ON oi.product_id = p.product_id
WHERE DATE_FORMAT(o.order_date, '%Y-%m') IN (
SELECT revenue_month
FROM (
SELECT
DATE_FORMAT(order_date, '%Y-%m') AS revenue_month,
SUM(total_price) AS monthly_revenue,
RANK() OVER (ORDER BY SUM(total_price) DESC) AS revenue_rank
FROM orders
GROUP BY DATE_FORMAT(order_date, '%Y-%m')
) ranked_months
WHERE revenue_rank <= 3
)
GROUP BY p.category, DATE_FORMAT(o.order_date, '%Y-%m')
ORDER BY revenue_month DESC, category_revenue DESCCharts, narrative, findings, and payloads are exactly what the platform produced, not a mockup.
Cross-source queries
Blend warehouses, ERPs, SaaS apps, and files in one question.
Auto-chart selection
Bars, lines, areas, scatter, maps, heatmaps, big numbers. Matched to the data.
Validated follow-ups
Suggested follow-ups carry pre-validated SQL. Click and skip nl-to-sql.
Explainable SQL
Every answer shows the exact query, inspectable, editable, with provenance.
Streaming results
Charts render as rows arrive. Narrative streams token-by-token.
Agentic SQL retry
A broken query is auto-corrected and re-run. You see “Adjusting…” not a red error.
Finance & FP&A
Variance analysis, close commentary, cashflow deep-dives auditors and boards can trust.
Revenue operations
Pipeline diagnostics, churn root-cause, segmentation, without a BI ticket.
Operations leadership
Throughput, quality trends, supply-chain anomalies. See what happened and why.
Your AI that protects.
Every transaction validated against every policy, in real time, every time. Block violations the moment they happen, not at the next audit.
Duplicate payments stopped. Segregation-of-duties enforced. Fraud flagged. The Governance Engine replaces sample-based audit with continuous 100% coverage and gives auditors immutable evidence.
Real-time policy engine
Business rules and regulatory controls evaluated on every transaction at ingest, not at month-end.
Duplicate + anomaly detection
Catches duplicate payments, invoice fraud, unusual vendor patterns, and SoD violations instantly.
Editable policies + history
Tune severity and rule JSON inline. Every change writes a before→after audit diff.
Immutable audit
Hash-chained, tamper-evident audit ledger. Exportable to your SIEM. SOC 2 / SOX ready.
Live sample · real data from the app database
Quality Notifications 4 viewed — List quality notifications (defects) that have been logged in the system
You now have visibility into 5 quality notifications representing defects logged in the system. All notifications are currently in 'New' status and were created by the same user, indicating they require immediate attention and processing.
Quality Notification 3 viewed — Retrieve quality notification with reference number 704 to get its long text description
The API call successfully retrieved quality notification data, but notification 704 was found with an empty LongText field. The detailed long text description you requested is not populated in the main record, though it may be available through a separate deferred navigation property.
Quality Notification 3 viewed — Retrieve quality notification with reference number 704
The search for quality notification 704 returned 4 records, but notification 704 specifically refers to "Cracked housings on HT-1000 units" with reference number ACME-PO-2026-1142, created by Admin Quadrazene and currently in 'New' status.
Quality Notification 704 created — "Cracked housings on HT-1000 units"
Quality notification 704 was successfully created in SAP, but the system returned empty values for all requested fields including NotificationType, ShortText, ReferenceNumber, and LongText, suggesting the creation may not have processed the input data correctly.
Charts, narrative, findings, and payloads are exactly what the platform produced, not a mockup.
Access review
Periodic certifications. Dormant accounts flagged. Privileged role drift detected.
PII exposure scan
Find and redact PII before it reaches a model, a reply, or a downstream system.
PO compliance audit
Frame contracts, three-way match, vendor-risk screens. At every PO, not in samples.
Segregation of duties
Four-eye principle enforced. Overrides require dual approval, captured to ledger.
Findings → Action Items
Resolve or escalate any finding into a tracked task with full provenance.
SIEM + GRC integration
Push to Splunk, Sentinel, Chronicle, or syslog with standard schemas.
Accounts payable
Stop duplicate payments, ghost vendors, and invoice fraud before the money leaves.
Compliance & audit
Continuous controls monitoring across SOX, GDPR, HIPAA, and sector regulations.
Security & access
Enforce SoD, data classification, and access boundaries across every system.
Your AI that guides.
Forecasts, scenarios, and prioritized recommendations with ROI quantified. Guidance that anticipates what comes next, and tells you what to do about it.
The Advisory Engine projects KPIs forward, simulates what-if scenarios, surfaces risks early, and converts every recommendation into an executable plan the Actions Engine can run.
Forward-looking forecasts
KPIs, cashflow, demand, and churn projected forward with calibrated confidence bands.
Scenario planning
What-if simulations across decision paths. See downstream impact before you commit.
Prioritized recommendations
Not every possibility. A ranked shortlist with ROI, effort, and risk attached.
Executable action plans
Every recommendation converts to a concrete plan the Actions Engine can run.
Live sample · real data from the app database
Run the at-risk classifier for project 662449. Show P(slip), the predicted slip-weeks for context, and the strongest positive drivers from the contribution breakdown.
| project number | customer | division | status | total tons | recent change count | late stage change pct | weeks since last change | milestone overdue pct | critical overdue count | division id | predicted slip weeks p50 | predicted slip weeks p90 | probability at risk |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 662449 | McCarthy Building | Bridge & Highway | ACTIVE | 295 | 7 | 0.143 | 5.286 | 0 | 0 | 2 | 0.19 | 0.19 | 0.412 |
The project 662449, under McCarthy Building in the Bridge & Highway division, has a notable probability at risk of 41.2%, indicating a significant chance of project delays. The predicted slip weeks are minimal at 0.19 for both P50 and P90, suggesting that while the risk is present, the expected delay is relatively low. The primary driver for this risk is the weeks since the last change, which stands at 5.29 weeks, hinting at potential stagnation in project progress.
- The probability at risk of 41.2% indicates a substantial likelihood of project delays, which is noteworthy for an active project.
- Despite the risk, the predicted slip weeks are only 0.19, suggesting that any delays may be minor in magnitude.
- The weeks since the last change at 5.29 weeks is the top driver for both the regression and classification models, highlighting a potential area of concern for project momentum.
Charts, narrative, findings, and payloads are exactly what the platform produced, not a mockup.
Quantified impact
Every recommendation declares dollars, ARR, units, or hours, with priority and timeframe.
Step-by-step plans
Each suggestion ships an executable plan, not a vague “consider improving X.”
Promote to Action Item
One click captures category, priority, owner, due date, and source provenance.
ML predictions
Gradient-boosted + logistic models drive explainable, SHAP-style driver waterfalls.
Forecasting + bands
Forecasts ship with confidence bands, not just point estimates, so risk is sized.
Cross-engine signal
Insights anomalies and Governance findings roll into Advisory's prioritization.
CFO / Finance
Rolling forecasts, cashflow scenarios, capital allocation, with assumptions visible.
Sales / RevOps
Pipeline quality signals, churn prediction, deal prioritization, territory planning.
Supply chain
Demand forecasting, inventory optimization, vendor-risk scoring, lead-time prediction.
Your AI that does.
From extracting data out of a PDF to posting a transaction in your systems of record. ERP, CRM, ITSM, HCM. The Actions Engine closes the loop from decision to execution, 24/7, fully audited.
User-initiated for high-judgment work. Autonomous for repetitive pipelines. Approval-gated for anything that matters. Every action attributed, every step journaled, every outcome explainable.
Interactive transactions
User-initiated actions with guided forms, approval routing, and confirmation. Right in chat.
Background pipelines
Scheduled and event-triggered autonomous workflows that run overnight and on weekends.
Document intelligence
Extract structured data from PDFs, scans, emails, and attachments, then route onward.
Close the loop
Every upstream decision becomes a traceable, reversible action in your systems of record.
Live sample · real data from the app database
Quality Notifications 4 viewed — List quality notifications (defects) that have been logged in the system
Charts, narrative, findings, and payloads are exactly what the platform produced, not a mockup.
NL → typed operations
Natural language resolves to typed create / update / invoke calls on any connected system. Validated before execute.
Normalized at the connector
OData, REST/OpenAPI, SQL, and MCP tools. Auth, pagination, date formats, and edge-case errors solved once, per connector.
Payload preview + edit
Every payload shown before send. Edit values inline if needed.
HITL gates
SLA-bound, audience-routed approvals with decision notes captured to audit.
ERP · CRM · ITSM · HCM write-back
SAP S/4 + ECC, Salesforce, ServiceNow, Workday, NetSuite, plus any REST/OpenAPI or MCP server. Same pattern.
Reversible + compensatable
Every action can be rolled back or compensated with full audit.
Accounts payable
Email-in vendor PDFs → extract → match → approve → post to your ERP. Days become minutes.
Revenue & CRM ops
Sync quotes, update opportunities, and write order status back to CRM. Approvals routed, every change attributed.
Service & IT ops
Triage inbound tickets, enrich from systems of record, then open or update ITSM incidents. Running on their own.
Closed-loop intelligence
Every Engine feeds every other.
No insight goes unprotected. No recommendation goes unexecuted. No execution goes unanalyzed. The compound gets smarter with every cycle.