Visible too late
The opportunity only comes into focus when the specifications are finalized. Strategic input on the setup is no longer possible.
A logistics service provider grows through new cargo flows. These are rarely announced clearly, but the early signals are traceable online.
A new distribution center, a factory expansion, or a shipper re-tendering its transport: each is an event made public months in advance, hidden within permits, annual reports, press releases or zoning plans.
Although this information is public, it is scattered across hundreds of sources, totaling over 200,000 unstructured pages of text and data. It is impossible for people to track manually, and certainly not every week.
In practice, Sales only learned about an opportunity once the formal tender was published, well after the ideal window to proactively influence the scope.
The opportunity only comes into focus when the specifications are finalized. Strategic input on the setup is no longer possible.
Permits, zoning plans, annual reports and news are fragmented, each written in its own context and jargon.
Manual searching takes hours every week and stays restricted to familiar clients and regions.
We built a dedicated AI pipeline: public sources are collected, read and classified by the model into actionable, relevant signals for Sales.
One updated overview of matched opportunities every week, in place of random, ad-hoc alerts.
The application does not determine who to call. It ensures that outreach is driven by what is happening in the market rather than by what happened to come along.
Want to know more about this?Every organisation works with AI, but everyone does it differently.
This case shows which phases of the Disruptiv framework another organisation went through. The assessment does the same for yours: you will not only see your score, but also which phase currently limits your progress and what needs to be done first.
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