Three predictive applications plus the developer reference. One predictive database underneath.
Open the demo closest to your domain — or scroll the use cases by capability. Same predictive operators across all four open-source demos. The three application demos showcase predictive ERP, accounting, and e-commerce in production-ready shape; the grocery demo at demo.aito.ai is the developer reference where the queries are visible end-to-end.
Three predictive applications plus one developer reference. Each runs against an Aito instance. Open the live demo to click through it, read the source on GitHub, or browse the full feature inventory on the per-demo page.

14 production-ready use cases across industrial maintenance, multi-channel retail, and professional services. 72% aggregate automation rate on the mixed profile.

Multi-tenant by construction. 255 customer companies, 128K invoices, one shared Aito instance. Same operators behind 95%+ accuracy Nordic enterprise AP automation since 2018.

16 views on a 110K-row PetNord pet-store dataset. Smart search, recommendations, demand forecast, win-back, plus a deliberate honest-failure case so calibration shows through.
A sampling of what predict, relate, search, recommend, estimate, and evaluate do in production-ready shape. Each card links to the demo that showcases it best. The full catalog is at /use-cases/.
Pattern discovery, calibration, forecasting, segmentation. The decisions a user makes after seeing the data.

Statistically significant co-occurrence and persona-affinity patterns, ranked by lift. Dog dry-food cross-sells to dental treats at 2.72× in the PetNord fixture, mined live.
See in demo →Source →
Discover statistical patterns (category=telecom & gl_code=6200 → approver=Timo, 15.8× lift). Promote to rules with audit trail; dismiss to record the decision.
See in demo →Source →
System scores its own predictions on held-out data. Return Risk reports +0.0 pp gain over baseline and renders as a red row.
See in demo →Source →
_predict units_sold blended with seasonality factors from same-month historical data. Drives replenishment without a separate forecasting model.
See in demo →Source →Search, recommendations, smart forms, conversational. The human stays in control; the system boosts speed and accuracy.

Persona-conditioned re-ranking. Same query returns different rankings for different shopper segments — derived from the data, not from a curated rule.
See in demo →Source →
Cross-sell ranked by lift, for-you tile rankings, bought-together pairs. All from the same predictive operators against the same data.
See in demo →Source →
Pick a supplier and four fields predict in parallel — cost center, account code, project, approver. Tab to accept, Esc to reject.
See in demo →Source →
CTR-ranked help articles via _recommend against click history. Users read what other users with similar queries clicked.
See in demo →Source →Categorization, routing, anomaly detection, multi-field prediction. Calibrated confidence decides what auto-processes and what routes to human review.

Every purchase order arrives with predicted account code, cost center, and approver — three confidence tiers, bulk-approve for rule-matched rows.
See in demo →Source →
GL code, approver, payment method, cost center predicted per invoice with $why factor decomposition. The full AP automation surface.
See in demo →Source →
Inverse prediction — low confidence on a normally-predictable field is the anomaly. Mis-coded account, amount spike, unknown vendor; surfaced before posting.
See in demo →Source →
Catalog gap-fill on workflow-blocking products. Predict category, HS code, unit price one-shot across the catalog. Same pattern as smart forms, applied to data rather than input UI.
See in demo →Source →Explore the complete source code, technical documentation, and performance benchmarks
{
"from": "impressions",
"where": {
"context.user": "larry"
},
"recommend": "product",
"goal": { "purchase": true }
}
Production-ready AI without the complexity of traditional ML infrastructure
Complete technical evaluation path for engineering leaders
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