A document tool tends to define success as: the user uploads a document, the tool produces correct structured output, the output appears on the screen. But that’s not where the user’s job ends. Their job ends when the extracted values are in the spreadsheet they actually maintain, or the system of record they actually use, or the memo they’re actually writing. The distance between “correct on the tool’s screen” and “usable in the user’s real workflow” is the last mile of the output, and it’s where a lot of otherwise-good tools quietly lose their value.

The failure is subtle because the tool genuinely did its core job. The extraction was accurate, the interface was clean, everything worked. But the user now faces a manual step: copying values out, reformatting them to match their template, re-keying them into another system, reattaching the context that the tool’s display had but the export didn’t. Each of those steps costs time and reintroduces the errors the tool was supposed to eliminate — a transcription mistake in the copy-paste is just as wrong as an extraction mistake, and now it’s the user’s fault instead of the tool’s. The tool saved effort in the middle of the task and gave it back at the end.

The last mile is especially treacherous because it’s invisible in a demo. A demo ends at the screen — the extracted values displayed cleanly, the audience nods, the tool looks done. Nobody watches the part where a real user has to get those values into the format their boss expects. So the last mile rarely gets built, because the thing that sells the tool doesn’t include it. But the thing that retains the tool absolutely does, because a user who has to manually bridge the last mile every single time is a user doing a chunk of the work by hand forever, and eventually questioning what they’re paying for.

Building the last mile means designing backward from the user’s destination, not forward from the tool’s output. What format does the result actually need to land in? What system does it need to enter, and does that system have an import path the tool can target? What context has to travel with the values — the citations, the source references, the units and qualifiers — so the output is usable and defensible once it’s out of the tool? Answering these turns the output from a display into a deliverable. It’s less glamorous than the extraction itself, but it’s the difference between a tool that demos well and a tool that disappears into the user’s workflow so smoothly they stop noticing it’s there.

The general principle: the value of a tool is realized at the point where its output meets the user’s real work, not at the point where the tool finishes computing. Optimizing everything up to the screen and stopping there leaves the hardest, most thankless, most adoption-critical part unbuilt. Walk the last mile — get the output all the way into the place the user lives — and you close the gap between a tool that’s technically impressive and one that’s actually used.