Insights
See the kind of work VaultData would do for you
Working VaultData demonstration projects below, built on synthetic and public sample data, plus two example dashboards from the industries VaultData works in most — a hotel booking view and a restaurant sales view. As VaultAI and VaultRide develop, insights from those divisions will land here too.
Technical & business case studies
Beyond the demos: full projects, start to finish
The dashboards further down are simplified previews. These are complete, working analytics products — methodology, validation, and all — that we designed, built, and deployed, using synthetic data for fictional businesses.
VaultData Business Intelligence Dashboard
From business data to actionable decisions.
An interactive analytics solution demonstrating how businesses can transform operational data into actionable intelligence through visualization, customer segmentation, forecasting, and predictive analytics.
- Executive KPIs with period-over-period revenue growth
- Transaction-level customer segmentation (k-means, silhouette-validated)
- Holt-Winters revenue forecasting with a time-ordered holdout validation (MAE/RMSE/MAPE)
- Illustrative inventory demand outlook with stockout/overstock risk flags
- Automated data-quality checks and a recommendations engine driven by the live data
Prairie Pulse E-Bikes Retail Analytics
Seasonal retail, forecast, stocked and financed to match.
An end-to-end analytics proof of concept for a fictional Calgary electric-bike retailer: a validated relational database, five predictive models, a double-entry financial module and a 17-page executive dashboard covering sales, margin, inventory, customers, the service workshop, three-statement financials and a 12-month financial forecast. Built on synthetic data anchored to real public e-bike prices and real Calgary weather; every financial figure is simulated.
- Validated SQLite model with 30 automated integrity and reconciliation checks
- Prophet, SARIMA and XGBoost forecasts compared on leakage-safe time-based backtests
- Seasonal reorder points tested in an out-of-sample replay against a flat stocking policy
- Simulated double-entry accounts: ~19,900 balanced journal entries, monthly trial balances and AR/AP sub-ledgers
- Income statement, balance sheet and cash flow that reconcile every month, with ratio and working-capital analysis
- Driver-based 12-month financial forecast with scenarios, sensitivities and a live-formula Excel model
Prairie Home Furnishings Analytics
Custom orders, deposits and design consultations, tracked from showroom to hand-off.
An end-to-end analytics proof of concept for a fictional Calgary furniture retailer selling stocked and made-to-order furniture: a validated relational database, demand forecasting, a double-entry financial module and a 14-page executive dashboard covering sales, product profitability, inventory, custom-order tracking, supplier performance, customers, design consultations, three-statement financials and a 12-month scenario forecast. Built entirely on synthetic data; every figure is illustrative.
- Validated SQLite model with 30 automated data-integrity checks and 11 financial reconciliation checks
- Custom-order tracker following deposits, supplier ETAs, promised dates and balances due before pickup
- Customer deposits held as contract liabilities, with revenue recognised at hand-off
- SARIMAX, XGBoost and seasonal-naive forecasts compared on time-based backtests
- Design-consultation analytics linking follow-up cadence and designer to conversion and order value
- Integrated 12-month forecast and scenario simulator, matched by a live-formula Excel model
Prairie Auto Care Analytics
Collision repair and car care across three branches, from first call to insurer payment.
An end-to-end analytics proof of concept for a fictional multi-location Calgary collision repair and car care group: a simulated repair workflow of about 25,000 repair orders, a double-entry financial model with work in progress and insurer direct billing, six predictive models and a 15-page dashboard covering job profitability, technician productivity, cycle times, parts, suppliers, insurance claims, branch comparison, three-statement financials and a capacity-aware 12-month forecast. Built on synthetic data with real Calgary weather; every figure is illustrative.
- Repair workflow simulated end to end: estimate, insurer approval, parts, technician scheduling, quality control, delivery and payment
- Job costing per repair order, with fully loaded profit and warranty rework traced back to the original job
- Technician utilisation, efficiency and productivity kept distinct, with fair comparisons adjusted for job mix and role
- Cycle-time bottleneck analysis, with model-estimated completion dates for open repairs
- Branch P&Ls with interbranch eliminations that sum exactly to the consolidated statements
- Capacity-constrained 12-month forecast and scenario simulator, matched by a live-formula Excel model
Featured project · live
US Election Intelligence
A live, open-source analytics app we built and maintain on public data — refreshed automatically every day.
Public-data project · nonpartisan
A nonpartisan polling and scenario analysis tool for the 2026 US Senate, House and governor races and past presidential elections, built entirely on public data. It shows what the polls say and what the seat arithmetic would be under assumptions you choose. It does not forecast winners or give probabilities of victory.
- Weighted polling averages with intervals, moving averages, LOWESS and a Bayesian (Kalman) trend
- Pollster house effects and likely-voter vs registered-voter comparisons
- Scenario simulator: national, regional and state shifts, undecided split, turnout and polling-error assumptions
- Electoral map with Maine and Nebraska district allocation and tipping-point analysis
Independent, nonpartisan project by VisiVault Analytics Ltd. Every scenario is a hypothetical calculation, not a prediction. Poll figures come from the cited public sources; verify important numbers there.
Example dashboards
Two simplified previews
Lighter, illustrative examples from other industries VaultData works in — try the filters below.
Hospitality demo
Room bookings by type
Try the filters below — this is a live example of the dashboards we build for clients.
Total bookings
143
vs previous period
+4.2%
Restaurant demo
Sales by meal period
Try the filters below — this is a live example of the dashboards we build for clients.
Day total
$8,980
Coming soon
Articles and guides
We're building out a library of short, practical guides on data, AI, and digital solutions for growing businesses. In the meantime, book a call and we'll answer your questions directly.
Want a dashboard like this for your data?
We'll build a working preview using a sample of your own data — no commitment required.