Real-time visibility for a farmer cooperative

A cooperative buys produce from thousands of farmers and pays them through M-Pesa.

Use case · how we solve it
01 · The challenge

What holds organisations back.

  • Reports compiled manually every week
  • No view of intake, payments and cash together
  • Hard to plan for peak seasons
02 · The solution

Pulse: Executive dashboards & forecasts.

Finance, sales and operations in one real-time view, with AI forecasts for what's next.

03 · How it works

The architecture.

About Pulse
SOLUTION ARCHITECTURE · PULSE REFERENCE DESIGN · v1.0 01 SOURCE SYSTEMS 02 INGESTION 03 DATA PLATFORM 04 CONSUMPTION SAP S/4HANA Finance · sales CRM & POS REST APIs M-Pesa Statements · API Data pipelines CDC · batch · stream Lakehouse Delta · bronze→gold Semantic model KPI definitions Forecasting ML models · MLflow Dashboards Power BI · mobile 1 2 3 4 5 6 7 8 PLATFORM, SECURITY & OPERATIONS Azure / AWS Entra ID SSO Data quality Governance
  1. 1Changes captured from SAP every hourCDC · OData
  2. 2Sales and customer data pulled inREST · incremental
  3. 3Payment statements loaded dailyAPI / SFTP
  4. 4Raw data lands in the lakehouseBronze layer
  5. 5Data is cleaned and modelled into KPIsSilver → gold
  6. 6Models train on history to forecastPython · scheduled
  7. 7Leaders see live dashboardsRow-level security
  8. 8Forecasts appear beside actualsScored tables
04 · How we deliver

Our lifecycle, step by step.

  1. Understand

    Agree the KPIs that matter most

  2. Design

    Connect ERP, intake and M-Pesa data

  3. Develop

    Build mobile dashboards for the board

  4. Review & test

    Add seasonal intake forecasts

  5. Deploy & manage

    Go-live with hypercare, then 24×7 support and monthly reviews.

05 · What changes
DailyKPIs instead of weekly reports
1 viewof intake, payments and cash
Forecastsfor peak-season planning
Target outcomes for this scenario. Actual results depend on each organisation's volumes and systems.

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