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In brief.
One scenario keeps repeating in companies: the internal document AI pilot impresses, then stalls between 70% and 80% accuracy. The reason: the first 80% is easy, carried by simple cases; the last points cost exponentially more, because the remaining errors live in the hard cases — scanned annexes, nested tables, cross-references, ambiguous wording. Yet below roughly 95%, experts have to reread everything, and the gain disappears.
The long tail of hard cases
The accuracy of a document system does not improve linearly with effort: the remaining errors concentrate in cases that are individually rare and collectively frequent. Correcting them means identifying them (fine-grained measurement), annotating them (mobilising subject-matter experts), and verifying that each fix does not break another (replaying full benches). Every point of accuracy gained costs more than the last.
The economic threshold is unforgiving
At 80% accuracy, one answer in five is wrong and nobody knows which: review has to be exhaustive, and the gain is limited to typing time. Value is only unlocked at the point where measured reliability permits review targeted on the answers flagged as fragile. That is a change of regime, not a gradual improvement. Hence the paradox of pilots: they succeed at the demonstration (which lives in the easy 80%) and fail at generalisation (which lives in the remaining 20%). A governance question before any rollout: “what measured accuracy, against which bench, and what costed plan to reach the targeted-review threshold?”.
The Optivalue.ai approach
Getting past that wall is Optivalue.ai’s permanent investment: models specialised by domain, continuous evaluation, and confidence scores that organise targeted review instead of exhaustive review.
Why do the last accuracy points cost so much?
Because they live in the long tail of rare cases, each requiring identification, annotation and regression testing.
Is 80% accuracy a failure?
Economically, yes: review remains exhaustive and the return on investment disappears.
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