AI for data and analytics, that people can check
OceanLab builds AI into forecasting and data operations: forecasts that explain themselves and monitors that catch bad data before it spreads. The model forecasts and flags; planners and data owners decide. Every example below is a product we built.
OceanLab product builds
AI products we designed and built in this industry. Each one is a full case study with screens, scope and the rules it was built for.
Garúa - Explainable Demand Forecasting for Grocery Planners
Designed and built a clickable demand forecasting platform for a Lima supermarket chain: daily SKU by store forecasts with an 80% band, a driver breakdown for every forecast, a weekly review where planners override with a reason inside approval limits, and a freeze before the export to replenishment.
Sukat - Data Quality Monitoring with Incidents and Circuit Breakers for a Hospital Group
Designed and built a clickable data quality and observability tool for a private hospital group with five hospitals in the Klang Valley and Penang: table monitors on the analytics warehouse, incidents with owners and response targets, downstream impact on dashboards, and circuit breakers that hold publishing when a critical check fails.
Where AI earns its place
Each use case names the builds that did it.
Demand forecasting
Daily forecasts per product and store with an 80% band and a breakdown of what drove each number.
Planner overrides
A weekly review where planners override a forecast with a reason, inside approval limits, then a freeze before the export to replenishment.
Data quality monitoring
Table monitors on the analytics warehouse, with incidents that have owners and response targets.
Circuit breakers
When a critical check fails, publishing is held and the dashboards downstream are shown as affected.
What to plan for
The rules that shape AI in this industry. General information, not legal advice: check with your own counsel.
Explain the number
Overrides with reasons
Stop bad data at the door
Personal data in the warehouse
From one workflow to production
- 01
Pick the workflow
We start from one workflow your team wants off its plate and agree what a working result looks like.
- 02
Clickable AI prototype
Your team tries the flow on a clickable prototype before any production code is written.
- 03
Production build
We build the production version, with the approval steps and records your industry needs.
- 04
Launch and improve
It goes live in your team's hands, and we tune it as real work runs through it.
Priced either way, whichever suits the work: outcome-based, paid per milestone, or hourly at $30-50 depending on role and seniority. More on AI automation →
Questions teams ask
What can AI do for a data or analytics team?
Forecast demand with the reasons shown, let planners override with a reason, and watch the warehouse so a failed check holds publishing before bad numbers spread. Each of these is a product OceanLab built.
Can planners overrule the model?
Yes. In our forecasting build planners override any forecast inside approval limits, with a reason, and the plan is frozen before it goes to replenishment.
How is it priced?
Either way, whichever suits the work: outcome-based, where you pay per milestone, or hourly at $30-50 depending on role and seniority.
Keep exploring
Are you an AI lab looking for human training or evaluation data? That is a separate offer, OceanLab Labs.
