Your retail data has answers.
RetailAi asks the right questions.
An AI-powered analytics platform that ingests sales, inventory and customer data from files or live databases, cleans it with machine learning, forecasts demand, and alerts you before stockouts happen — all on autopilot.
pulled live from the RetailAi PostgreSQL warehouse just now
Dashboards that answer before you ask
These aren't mockups — each chart below queries the RetailAi API and its Postgres warehouse the moment you load this page.
Revenue & Profit Trend
Monthly, entire history
Inventory Health
SKU status right now
Revenue by Region
All-time contribution
Top Products by Revenue
Best sellers across the catalog
Don't take our word for it. Run the models yourself.
Each panel below executes a real scikit-learn model on the server the moment you press the button — the same models that clean, segment and forecast your data in production.
Revenue Forecasting
A regression model fits the full revenue history and projects it forward — reporting its own error rate (MAPE) so you always know how much to trust it.
Anomaly Detection
Every ingested batch passes through an Isolation Forest that spots impossible transactions — spikes, glitches, broken margins — and quarantines them before they poison your dashboards.
Customer Segmentation
No one labels customers by hand. A clustering model groups them by order frequency and lifetime spend, then ranks the clusters into VIP, Returning and New — watch it assign every customer live.
Data flows in. Decisions flow out.
Every ingestion — manual upload or a scheduled Apache Airflow job — moves through the same four-stage pipeline, fully automatically.
Extract
CSV / Excel uploads, or live pulls straight from your existing databases with column mapping — no manual exports.
ML Transform
Anomalies quarantined, missing values imputed by regression, customers auto-segmented — with a before/after preview of every batch.
Load
Clean records land in the PostgreSQL warehouse, instantly powering every dashboard, forecast and report.
Validate & Alert
Stock thresholds re-checked on every load — low-stock and overstock alerts fire within minutes, not days.
orchestrated by Apache Airflow · nightly sales ingest · hourly inventory sync · weekly model retraining
Inside the platform
Real screenshots from the running RetailAi dashboard — not concept art.
A complete platform, not a proof of concept
Fourteen production capabilities, working end to end today.
Role-based access
Admin & Business User logins with JWT auth and full audit trails.
File upload ETL
Drag-and-drop CSV or Excel for sales, inventory and customers.
Database connectors
Pull straight from external Postgres databases with column mapping.
ML data cleaning
Anomaly detection, missing-value imputation and auto-segmentation on every batch.
Before/after preview
See exactly what the ML changed in every pipeline run — no black boxes.
AI forecasting
Revenue projections with self-reported accuracy, retrained on schedule.
Demand risk
Per-product stockout risk from predicted demand vs. stock on hand.
Smart alerts
Low-stock and overstock notifications the moment thresholds are crossed.
Live dashboards
Sales, revenue, profit, inventory and customer analytics in real time.
Automated reports
Daily, weekly and monthly rollups, exportable to Excel and PDF.
Airflow orchestration
Nightly ingest, hourly inventory sync, weekly model retraining.
Audit & monitoring
Every login, upload and export logged; every pipeline run tracked.
BI-tool ready
Read-only reporting views for Power BI, Tableau or any SQL tool.
Cloud-scale path
GCP-ready: Cloud Run, Cloud SQL, BigQuery and Cloud Composer.