Bretton AI

Bretton's pitch is arithmetic rather than novelty. Growing a bank's front office has meant growing the back office alongside it, and BPO contracts are how most institutions bought that capacity. Bretton sells the same capacity as agents running over the bank's own data, policies and SOPs, priced against cost per outcome rather than per seat. That framing is why the customer proof points matter more than the feature list: an FDIC-insured bank cutting compliance review time 87%, an OCC-regulated bank cutting EDD queue completion 70%, a global exchange at $5.35M first-year savings, a payroll platform at 84,000 hours saved annually in merchant operations. The build surface is deliberately shallow. Templates gives you 30+ pre-built skills and agents across 180+ data sources. Builder is now a guided, conversational workspace for custom agents covering checks, narratives, transaction mappings and disposition groups, with structured output controls so you can shape what an agent returns for APIs, exports and connected systems and validate it before saving. Workbench is the analyst-facing half: a shared case workspace where humans and agents work the same queue, with the Transactions view showing every row and column of an uploaded transaction file, search, column-level filtering, filter-aware totals and highlighting for alerted activity. What separates Bretton from a generic agent framework is the Trust Infrastructure underneath. Every decision is logged with reasoning, evidence and model version — the artifact a model risk or internal audit function actually asks for. Independent model validation, zero-data retention, SOC 2 Type II, GDPR and virtual private cloud deployment are the table stakes; the interesting piece is the Evaluator, the engine that measures whether agents still meet their standard run after run. Bretton published its own V2-versus-V1 grading showing 37% fewer errors on individual EDD and 23% on company DD with no added run time, which is a more useful signal than a benchmark screenshot. Where it fits: financial-crime and compliance teams at regulated institutions with high-volume alert, EDD, KYB, customer review, sanctions and transaction monitoring queues. Where it doesn't: anyone whose bottleneck is upstream data quality or case intake rather than reviewer throughput; teams that want to self-host an open API-first framework they build themselves; and non-financial organizations where model risk management isn't a requirement. Bretton also pairs agents with forward-deployed engineers and SMEs through Managed Services, which means deployments are guided rather than hand-it-over-and-hope — worth knowing if you were expecting to configure everything yourself.