Commercial offers were often prepared under time pressure, leading to optimistic assumptions and unclear boundaries that later caused margin erosion and customer conflicts, so ARP Ideas delivered an AI-based offer review agent that flags risks and underestimations before proposals are sent, improving pricing discipline and internal alignment.

Before the project, offers were frequently prepared under tight deadlines and relied heavily on optimistic assumptions, such as reusing a customer’s existing code without validation, treating an iOS version as a simple cosmetic change to Android, or assuming data migration would work without dedicated budget or effort.
These assumptions often remained implicit, leading to reduced margins after contract signing and conflicts with customers around statements like “but it was supposed to be included in the price”.
ARP Ideas designed an AI-driven solution acting as an “offer guardian” that reviews commercial offers before they are sent.
The agent reads the full offer context, including scope, man-day budget, assumptions, and schedule, and compares it against known delivery risks captured from prior projects and expert knowledge.

The system automatically detects common pitfalls such as missing buffers for integration or migration, promises of free platform ports, or dependencies on customer data that are not described or priced.
It flags potential underestimations by comparing entered effort with typical delivery ranges, for example, highlighting when a functionality that usually requires more than 10 MD is priced at 3 MD.

Each identified risk is returned with a concrete recommendation, such as adding a dependency clause on client API availability or introducing separate pricing for an iOS version.
A designated person, typically an architect or delivery lead, reviews these alerts and decides whether to accept or reject them, allowing the organisation to continuously build and refine its internal risk knowledge base.

After implementation, sales and delivery teams shared a common language of risk, reducing reliance on a single senior expert who previously “sensed danger” based on experience alone.
Importantly, the solution did not slow down sales activities but supported them by providing precise wording and justifications, enabling teams to add small clarifying statements that protected scope and pricing without weakening the commercial message.