Unified commercial records
Create reliable definitions and pipelines for product, sales, customer, partner, and regional data without hiding source differences.
Commercial intelligence
Agdali builds systems that turn fragmented commercial data into a usable view of products, customers, channels, and regions. The result is not another disconnected dashboard: it is a data product shaped around the decisions your commercial team needs to make.
Useful signals often exist, but they are split between spreadsheets, partner reports, loyalty activity, operational systems, and local knowledge.
Create reliable definitions and pipelines for product, sales, customer, partner, and regional data without hiding source differences.
Design views for specific questions—such as product movement, channel performance, participation, or regional gaps—rather than generic chart collections.
Connect programmes, submissions, receipts, rewards, and partner activity to the commercial picture they are intended to improve.
Make uncertain, incomplete, and conflicting records visible so teams can correct them before they drive a decision.
We identify who will use the information, which decisions recur, and what evidence those decisions currently lack.
We trace sources, definitions, ownership, gaps, and quality constraints before promising a unified view.
We build the collection, review, analysis, and reporting experience together so insight can become part of everyday work.
Relevant work
Baumit Klub keeps receipt evidence attached to structured product records and gives the team a clearer view across regions and sales channels.
Read the commercial intelligence case studyA dashboard may be one interface, but the harder work is collecting, defining, checking, and connecting the underlying records. We treat the complete workflow as the product.
That is a common reason to build a focused data product. The design can use partner feeds, field activity, loyalty participation, submissions, or other permitted sources to improve visibility without pretending unavailable data exists.
No. We can begin with a bounded decision and a small number of sources, while making data gaps explicit and leaving room for a stronger platform over time.
Bring the question and the data sources your team currently uses. We will map a practical path from fragmented records to a useful decision system.