Bretton AI vs Sardine (2026)

API first with self service webhook configuration and integrations into chain analytics (Chainalysis, TRM Labs) and screening data sources; used to consolidate risk stacks at enterprises like GoDaddy. Breadth of out of the box third party connectors is narrower than horizontal platforms; one user review requests more vendor integrations.

No-code rule builder over 4,000+ signals and custom data fields, flexible rules and automated workflows, ML models, and a suite of agents acting on rule and workflow outcomes. Orchestration of risk workflows is the core product motion.

Real time transaction monitoring is the core trigger surface; alerts, alert SLAs, and self service webhook configuration for event driven data flows. Agents act on incoming alert streams continuously.

Grounded in first party risk data rather than documents: 2.2B+ profiled devices, consortium fraud intelligence across industries, billions of device, behavior, identity, and transaction data points, plus screening data (OFAC, EU, UN, PEP, adverse media) and crypto chain analytics integrations. Agents reason over this network context.

Customer Profiles page provides a unified, searchable record of customer activity and lifecycle data, and the device/behavior network carries longitudinal history. Durable agent level memory across investigations is not documented as a first class feature.

Agents execute within analyst approved configurations: Sanctions Agent triages alerts per pre-configured dashboard settings, agents surface recommendations analysts validate, unified case management workspace, alert queues with SLAs and review windows. Human oversight is explicit in the product design.

Enterprise controls documented: user-scoped AI agent workspaces (private by default), expanded IP allowlisting with CIDR and IPv6, granular resolution trails, and deployment at regulated banks and 300+ enterprises across 70 countries. Formal certification list (SOC 2 / ISO) not surfaced in public docs.

Audit trails are a design center: audit-ready agents, signal-level AML resolutions for clearer audit trails, alert SLAs with status duration tracking, SardineQL read-only SQL access to user/session/transaction data, and dashboards. Regulatory transparency is a stated product requirement.

API first cloud platform with self service webhooks and dashboard IP allowlisting; integrations with chain analytics providers (Chainalysis, TRM Labs). Multi tenant SaaS only; no on premise or private cloud deployment documented. A user review notes wanting more vendor integrations.

Pre-built rulesets ship for identity verification, payments, counterparty risk, and AML, alongside purpose built agents (KYC Onboarding, Sanctions/PEP/adverse media, transaction monitoring, SAR drafting). Productized for fraud and compliance jobs out of the box.

Runs proprietary ML models trained across billions of sessions plus LLM based agents; user facing model choice or bring your own model is not documented. Model flexibility sits with the vendor, not the customer.

Extensible via custom data fields in the rule builder, self service webhooks, SardineQL read only SQL (preview), and API first integration. Extension happens through configuration and data surfaces rather than a plugin SDK.

Rule backtesting is documented by users as a differentiator (build rules without retraining a model, then backtest), which is evaluation tooling for the automation layer. Formal agent evaluation or simulation framework beyond rule backtesting is not documented.

Compliance is the product: KYC/KYB, AML transaction monitoring, sanctions/PEP/adverse media screening, CDD risk tiering, SAR drafting and filing, case management, and audit ready agent trails, deployed at regulated banks. Built explicitly for BSA/AML regulatory workflows including the 2026 Nacha mandate.