Greenlite

Bretton AI is an agentic operations platform built for the financial back office — banks, fintechs, payment platforms, and exchanges that want casework capacity without adding headcount every time the front office grows. The pitch is blunt: for 100 years, growing a bank meant growing its back office alongside it, and Bretton argues AI-native operations break that arithmetic. It layers over the data, policies, and tools you already run rather than replacing them. The platform has four visible parts. Templates ship 30+ pre-built skills and agents plus 180+ native data sources for document reviews, alert handling, customer reviews, due diligence, case narratives, and core systems. Builder turns natural language into custom agents trained on your own policies and SOPs. Workbench is the shared workspace where analysts and agents work the same case, keeping a human in the loop. Underneath sits the Trust Infrastructure, which logs every decision with reasoning, evidence, and model version, then runs agent-as-a-judge QA/QC so production traces become eval sets. Quality measurement is where Bretton puts its weight. Bretton Evaluator scores agents continuously on live production runs, and in an October 2026 internal evaluation Agent V2 cut individual enhanced due diligence errors 37%, company due diligence errors 23%, and V1's errors by 30% on shared subjects. Bretton's post-Agent-in-a-Day path validates new agents against already-closed investigations while integrations are built in parallel. Named customers include Coastal Community Bank, Gusto Bank, and MVB Bank, and Bretton publishes outcomes rather than adjectives: 87% compliance review time reduction at an FDIC-insured bank, 70% faster EDD queue completion at an OCC-regulated bank, $5.35M first-year savings at a global exchange. It sits alongside your compliance stack as an operating layer, not a rip-and-replace platform.