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Your data already exists. Make it readable at last.

Overview

Dashboards, KPIs and analytics that answer the questions you actually ask.

A business dashboard consolidates the data scattered across your tools — sales, production, accounting, customer service — into readable, up-to-date indicators. For an SME it is the shortest path to steering with facts instead of gut feeling, without hiring a data team. MAWT builds dashboards connected to your existing systems, extended with analytics and machine learning where they provide a useful answer.

Target

For Swiss SME owners and managers who make decisions from hand-crafted Excel exports, contradictory numbers or intuition — while the data already exists in their tools.

Details

Most SMEs don't lack data: they have it everywhere — ERP, POS, e-commerce, accounting, spreadsheets. What's missing is a consolidated, reliable view. What does this customer really cost? What margin on this product line? Why is this month weaker?

We connect your existing sources, clean and cross-reference the data, and build the dashboards that answer your real questions. Python and machine learning come in when they bring something concrete: cash-flow forecasting, anomaly detection, image analysis on the production line. No big data for its own sake — answers.

The real problem is not a lack of data

Every tool in your company produces numbers. But each keeps them to itself: the ERP ignores the POS, accounting arrives a month late, and consolidation happens by hand in a spreadsheet, every Monday, done by someone with better things to do.

The result: decisions made on gut feeling, contradictory numbers in meetings, and weak signals — a customer drifting away, a margin eroding — noticed months too late.

Our approach: start from your questions, not the technology

We start from the decisions you make every week and the questions that remain unanswered. Those define the indicators — not a catalogue of standard charts.

Only then comes the technical work: connecting sources, making the data reliable, automating updates. Your teams type nothing: the dashboard fills itself, continuously.

When analysis goes further: forecasting and machine learning

Once the data is consolidated, some questions call for more than a chart: what cash position in three months? Which customers are at risk of leaving? Is this part off the production line compliant? That is where data science and machine learning earn their keep — in Python, on your data, with measurable results.

We stay pragmatic: a predictive model is only justified if it changes a decision. A lot of value already comes from data that is simply clean and visible.

What it includes
  • Connection to your existing tools (ERP, POS, e-commerce, accounting)
  • Data cleaning and consolidation
  • Real-time dashboards, at the office and on the go
  • Business KPIs defined with you
  • Advanced analytics and machine learning (Python) where useful
  • Automatic alerts on critical thresholds
Deliverables
  • A consolidated dashboard, continuously up to date, with zero manual entry
  • Indicators defined from your actual decisions
  • Data cleaned and made reliable at the source
  • Alerts on the thresholds that matter
  • Predictive analytics where they change a decision
Takeaways
  • Your data already exists — we make it consolidated, reliable and readable.

  • KPIs start from your questions, not from a chart catalogue.

  • Automatic updates: nobody re-types anything.

  • Machine learning and forecasts where they change a decision, not for show.

You might also need

Smart CRM

AI augmented CRM, built for your business, wired into your tools.

AI automation

Business and AI automation that frees your team from repetitive work.

Enterprise RAG

RAG on your knowledge base so AI answers with your context, not in general.

Frequent questions

How much does a business dashboard cost?

A first dashboard connected to two or three sources is up and running in a few weeks, for a few thousand francs. The investment then grows with the scope — additional sources, advanced analytics — always in stages priced upfront.

Do we need to change our tools to get dashboards?

No. We plug into what you have: ERP, POS, online shop, accounting, even spreadsheets. That is precisely the point — consolidating what is scattered, without disrupting how your team works.

Our data is messy. Is that a blocker?

It is the starting point of almost every project we do. Cleaning and reliability work are part of the job: duplicates, inconsistent formats, partial histories. We fix these at the source so the dashboard stays trustworthy over time.

How is this different from Power BI or an off-the-shelf BI tool?

BI tools are excellent displays, but someone has to connect, clean and model the data behind them — that is 80% of the work. We do that 80%, and use whichever display tool fits your context, including Power BI if you already have it.

Is machine learning useful for an SME?

Yes, on precise cases: sales or cash-flow forecasting, anomaly detection, quality control through image analysis. We only propose it when the expected gain clearly exceeds the cost — and never before the data is clean.
Next steps

Steer with facts, not gut feeling.