AI & Data

Know what you will needbefore you runout

Machine-learning forecasts for demand, stock and capacity — retrained on a schedule, reporting their own accuracy, and delivered inside the systems your planners already open.

Test a forecast See the results

Per branch, per SKU: Granular forecasts that reflect local seasonality, promotions and holidays.
Self-reporting accuracy: Every forecast tracks its own error so trust is earned, not assumed.
Embedded: Reorder and staffing recommendations inside ERP, POS or planning tools.
6–10 weeks: From data audit to first live forecast.

31%: Less waste
22%: Fewer stock-outs
92%: Forecast accuracy

Overview

Most forecasts fail becausethey live in a spreadsheet

A planner builds a careful model once, then it ages quietly while the business changes around it. Promotions, new branches, supplier changes — none of it makes it back into the model, and the forecast becomes a formality.

We build forecasts that retrain on fresh data, report their own accuracy, and appear where orders and rotas are actually made. The forecast changes the purchasing decision instead of sitting in a report nobody opens.

Who this is for

Multi-branch retail, hospitality and distribution businesses managing perishable or high-value stock
Operations teams planning staffing, fleet or production capacity
Finance teams who need demand-driven cash and inventory planning

4: Forecasting models live in Kaidova platforms
6–10 weeks: From data audit to first forecast

Two engineers reviewing a dashboard on a monitor

What's included

What you get from thisengagement

Working software and a documented reason for each decision — not a slide deck of possibilities.

Data readiness check
An honest view of whether your sales history, calendar and promotion data can support a reliable forecast yet — and what to fix if not.
Demand forecasting
Per-branch and per-SKU predictions that account for seasonality, promotions, weather and holidays, at the horizon your decisions need.
Inventory planning
Recommended order quantities that balance stock-outs against waste, cash tied up and supplier lead times.
Capacity & staffing
Forecasts that turn expected demand into shift plans, fleet allocation and production schedules.
Embedded in your tools
Predictions and recommendations delivered inside your ERP, POS or planning screens — not a separate app.
Accuracy monitoring
Drift detection, error reporting and scheduled retraining so accuracy holds month after month.

Our approach

From data todecisions, in threephases

Each phase ends with something you can review and a decision point where you can stop.

Start with a data check

- Audit sales, stock, calendar and promotion history
- Quantify current waste, stock-outs or overtime
- Choose the first scope (branches, categories, horizon) and accuracy metric
- Fixed-scope plan and estimate
You end up with: A go/no-go recommendation with a measurable target and a number.
- Data pipeline and features built and documented
- Model trained and back-tested against history
- Shadow run alongside current planning to prove accuracy
- Embedded into the ordering or rota screen with planner override
You end up with: A live forecast planners can see, compare and act on — with accuracy visible.
- Scheduled retraining and drift alerts
- Outcome tracked against the phase-one target
- Rollout to more branches, categories or planning areas
- Handover of pipelines and runbooks
You end up with: Forecasts that stay accurate as the business changes — and measurable savings.

Not sure which service you actually need?

Describe the problem in thirty minutes and a solution architect will tell you — including when the answer is that you do not need us for this.

Book a call

Tools we use

Forecasting built on proven tools

Established forecasting libraries and pipelines your data team can maintain.

Modelling
- Python(Prophet, XGBoost, statsmodels or similar)
Data
- PostgreSQL
- MySQL
- Pipelines
Runtime
- Docker
- AWS
- Azure
- Scheduled jobs
Delivery
- ERP / POS integration via API— Odoo, custom systems

Why us

Why forecast with Kaidova

Forecasting runs live in our own platforms for real operators. We have seen what breaks a forecast in a real kitchen or warehouse.

Proven in operations
Our forecasting models run in production for real businesses, not in a notebook.
Accuracy you can see
Every forecast reports its own error; planners keep the override and see when to trust it.
Decision, not dashboard
Recommendations land in the ordering or rota screen where the decision is made.
Honest about readiness
If your data cannot support a model yet, phase one tells you exactly what to fix first.
Built to be handed over
Pipelines, features and retraining runbooks documented for your team.

Our work

Results from systems in production

How disciplined engineering translates into operational outcomes. Every figure shown is measured on a live system and approved by the client.

View all case studies

01Lieferfair
Marketplaces & Logistics
Rebuilding a delivery marketplace to survive its own growth
A fast-growing delivery platform was hitting the limits of its original architecture. We re-engineered the core system for scale, reliability and real-time operations.
Read case study
3.2×
Increase in order throughput
02Construction contractor (on Oplyra)
Construction & Trading
One ledger for a contractor running six disconnected systems
Read case study
40%
Less time closing the month
03FastestVPN
Consumer Software
Scaling a consumer VPN to millions of sessions a day
Read case study
99.9%
Uptime across regions