3 Document Intelligence AI Agents, Live in Production.

Long documents break the tools used on them in ways that are easy to miss. A summary produced in one pass over a hundred pages is weighted toward whatever fitted in the window, so it reads as complete and systematically under-represents the second half. Translation done section by section without shared terminology renders the same term differently in different places, which is individually defensible and collectively unusable. And version comparison produces a diff — every changed character, four hundred entries, formatting and substance in one list — which shifts the work rather than doing it, because someone still has to read all of it to find the three changes that matter.

These agents are designed around each of those failures. Document Summarization produces a structured summary with key metadata and topics, processing long documents section by section with rolling context so later sections are summarised knowing what preceded them. Document Translation translates section by section carrying terminology forward, so the whole reads as one piece rather than a set of fragments. Document Comparison compares two versions and lists every substantive change, separating what alters meaning from what only alters wording. That separation is the difference between a comparison and a diff, and it is the reason a reviewer can read the output in a few minutes rather than treating it as a second document to work through.