Real-time product intelligence
An initial screenshot-upload brief became a native product for understanding ride-offer economics while the decision still matters.
Capture · Card-local recognition
Explicit calculations · Deferred AI enrichment
Native iPhone app · Offer review and history
After building the original upload application, Dimas began driving rideshare himself. That experience exposed a timing problem. He proposed shifting the product toward economic context at the offer decision, secured the founders’ agreement, and carried the rework through design and implementation.
The work connected field research, product and UX, native iPhone development, recognition, calculation, background processing, and organic distribution. Agents, specialized skills, and pipelines supported Dimas’s delivery work.
Recognition, calculation, and the driver’s choice have distinct responsibilities. Visible offer terms and configured vehicle costs support explicit projections; enrichment can follow later. Native extraction was treated as an evaluation question, with technical direction revised when device evidence challenged the initial assumptions.
The case includes implemented components and dated test and device records. It does not establish a fully verified public release or improved driver earnings. A complementary vehicle-services network is a proposed commercial direction.
Selected experience of BuildFutures founder Dimas. Adapted from the owner’s September 2026 case records; project stage and responsibilities are stated for this engagement.
Bring an early idea, a defined brief, or a system that needs to work better.
Your first step
Define the problem, the first useful scope, and the decisions needed to build it.
