Trunk Tools’ stack cut document review from 60 days to 10 by ditching general-purpose models

Most verticals aren’t clean, well-oiled SaaS databases; the reality is ugly documents, proprietary schemas, implicit workflows, and long‑running tasks that most general-purpose models struggle with. This prompted construction project management company Trunk Tools to build a specialized, three-layer architecture —… Most verticals aren’t clean, well-oiled SaaS databases; the reality is ugly documents, proprietary schemas, implicit workflows, and long‑running tasks that most general-purpose models struggle with. This prompted construction project management company Trunk Tools to build a specialized, three-layer architecture — perception, semantics, agents — based on highly-detailed data to support high-accuracy, highly-relevant industry automation.Their purpose-built stack has shrunk review cycles from months to days, prevented costly field errors, and given autonomous agents the ability to reason over millions of pages of documentation, Trunk says. “We really set out to take the data from dispersed systems, pre-process it, structure it, go through our ontology into a knowledge graph, and then train AI models,” said Sarah Buchner, Trunk’s founder and CEO and a former carpenter. For builders in other verticals, Trunk’s approach could serve as a blueprint for transforming data chaos into agent‑ready, industry-specific workflows. Where general-purpose LLMs break down on industry data Foundation LLMs, while powerful, are optimized for breadth, not…