Can we trust the figures in the drafts?

The app takes the figures straight from your systems and names their source, so controllers can check every number. Nothing goes to management without their release.

How quickly is the first app in production?

A first version of a simple app runs within hours, a complete one within days, depending on the systems you connect. In the AI Bootcamp your teams build their first apps with us in five days and roll them out.

Does Operaide work with our existing systems?

Yes. There is no connector catalogue to wait for: each connection is built for your system through REST or MCP, including ERP, CRM, EDI, portals, older and in-house systems. Connections are set up once in the platform, and your apps read and write through them with the access rights you set, without secrets in the code.

Does our data leave the company?

Only if you decide so. Operaide runs on your own infrastructure, and for each step of an app you choose the AI model: a local model on your own hardware for data that must not leave, or a frontier model in your cloud tenant. An app can also use a local model to remove personal data before anything reaches a cloud model. Every run is traced, so you can see which data went where.

Which data does the forecast need?

Your sales order history from the ERP, the longer the better. Promotions, prices, listings and holidays make it more precise.

How do we know the forecast is right?

Every forecast is measured against what actually sold, article by article. Your planners see the error next to each number and how it develops.

Does it replace our planning system?

No. The forecast goes into your ERP or planning tool, and your planners stay in charge of every number.

Domain experts build no-code in the App Builder, and developers extend the apps in code in Operaide Studio. IT keeps control of AI models, data and access. If you like, our engineers build the first version with you, for example in the AI Bootcamp.

Which AI models can we use?

Commercial, European and self-hosted AI models: OpenAI, Anthropic, Mistral, Azure, Google, Amazon Bedrock, OpenRouter and more, or open-source models via Ollama or LM Studio. Your administrators configure them, and every step of an app can use its own AI model, chosen for its task.

A forecast you can explain.From order intake, backlog and history.

Revenue by product group, region or customer. AI forecasts sales from your ERP order history and backlog, and explains every gap to the plan.

Talk about your process More for Controlling & Reporting

Trusted by leading enterprises

The challenge

Sales says plus eight. The order book says otherwise.

Forecasts are built in spreadsheets from sales input and experience. The order history in the ERP goes unused, and the gap shows up at the quarterly close.

Rolling_Forecast_Q4_v7_CFO.xlsxLast edited by Controlling, today 07:12

E4fx=Q3_Actual!E14*1.05

	A	B	C	D	E	F	G
1	Product group	Oct	Nov	Dec	Q4	FY 2027	Note
2	Industrial pumps	€1.4m	€1.5m	€1.9m	€4.8m	€19.6m	Sales: +8 % (new key account)
3	Valves	€0.9m	€0.9m	€1.0m	€2.8m	€11.2m
4	Drives	€0.6m	€0.7m	€1.6m	€2.9m	#REF!	big project Dec?
5	Spare parts	€0.8m	€0.8m	€0.8m	€2.4m	€9.6m	copied from budget
6	Service contracts	€0.5m	€0.5m	€0.5m	€1.5m	€6.0m
7
8

Forecast vs actual revenue 2025PlanActual

JanFebMarAprMayJunJulAugSepOctNovDec

ERP_RevenueSales_InputRolling_FCBudget_2026+

The solution

Every product group forecast, every gap explained.

Clear figures go into the rolling forecast. Controlling and sales settle the gaps.

Sales forecast14 product groups · 2 to review

Product groups

Q4 2026 and FY 2027 · from ERP order history

Industrial pumpsSales +8 %, forecast +2 %
ValvesOn plan
DrivesLarge project in Dec uncertain
Spare partsSteady after-sales business
Service contractsOn plan

Industrial pumpsYour decision

Year-end ordersPrice increase Jan

AprMayJunJulAugSepOctNovDecJanFebMar

ActualForecastRange

Why this forecast

Order intake trend−4 %
Year-end orders+12 %
Price increase Jan+3 %

Your decision

Sales input: +8 % for FY 2027
Forecast: +2 %, from order intake and backlog

Released figures go into the rolling forecast and the budget.

Release to forecastDiscuss with sales

The solution

Every product group forecast, every gap explained.

Clear figures go into the rolling forecast. Controlling and sales settle the gaps.

Sales forecast14 product groups · 2 to review

Product groups

Q4 2026 and FY 2027 · from ERP order history

Industrial pumpsSales +8 %, forecast +2 %
ValvesOn plan
DrivesLarge project in Dec uncertain
Spare partsSteady after-sales business
Service contractsOn plan

Industrial pumpsYour decision

Year-end ordersPrice increase Jan

AprMayJunJulAugSepOctNovDecJanFebMar

ActualForecastRange

Why this forecast

Order intake trend−4 %
Year-end orders+12 %
Price increase Jan+3 %

Your decision

Sales input: +8 % for FY 2027
Forecast: +2 %, from order intake and backlog

Released figures go into the rolling forecast and the budget.

Release to forecastDiscuss with sales

Impact

No surprises at the close.

Measured with you, in your process.

Without Operaide

Plans are built from spreadsheets and experience, and demand swings are spotted late.
Nobody can say where a number came from.
Controllers spend days collecting and merging sales input.

With Operaide

AI forecasts demand from your sales order history in the ERP.
Every figure shows its drivers and its source.
Controllers review the gaps, the rest is ready.

Why Operaide

Agentic AI is easy to start. Hard to run.

Operaide runs it in your company, under your control.

See the platform

Runs where your data is

On your own infrastructure, with the AI models you approve.

Every step traceable

Each decision is logged with its inputs. IT and audit see the full trace.

Grows with you

Live in days. From one automation to a complete application, on one platform.

FAQ

Questions about demand forecasting.

Want this for yourself?

Tell us about your process. In a demo we show you Operaide and how it would run it.

Talk about your process

More use cases

A forecast you can explain.From order intake, backlog and history.

Sales says plus eight. The order book says otherwise.

Every product group forecast, every gap explained.

Every product group forecast, every gap explained.

No surprises at the close.

Agentic AI is easy to start. Hard to run.

Runs where your data is

Every step traceable

Grows with you

Questions about demand forecasting.

Want this for yourself?

More for Controlling & Reporting.

Monthly reporting

Variance commentary

All for Controlling & Reporting

A forecast you can explain.From order intake, backlog and history.

Sales says plus eight. The order book says otherwise.

Every product group forecast, every gap explained.

Every product group forecast, every gap explained.

No surprises at the close.

Agentic AI is easy to start. Hard to run.

Runs where your data is

Every step traceable

Grows with you

Questions about demand forecasting.

Can we trust the figures in the drafts?

How quickly is the first app in production?

Does Operaide work with our existing systems?

Does our data leave the company?

Which data does the forecast need?

How do we know the forecast is right?

Does it replace our planning system?

Who builds the apps?

Which AI models can we use?

Want this for yourself?

More for Controlling & Reporting.

Monthly reporting

Variance commentary

All for Controlling & Reporting