Bretton AI vs Sardine (2026)

API first, with self service webhook configuration and integrations into chain analytics (Chainalysis, TRM Labs) and screening data sources, and used to consolidate risk stacks at enterprises like GoDaddy. No broad catalog of out of the box third party connectors is documented.

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.

Not established from the vendor's evidence. User scoped agent workspaces, private by default, and IP allowlisting with CIDR and IPv6 are described, but no SSO, role based access or certification such as SOC 2 or ISO is documented publicly.

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.

Not established from the vendor's evidence. No hosting provider, region, or on premise or private cloud option is documented.

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.

A customer can create, test and roll out monitoring rules without engineering support, and the Rule Assistant Agent tunes thresholds against alert quality and fire rates. A formal agent evaluation or simulation framework beyond rule testing is not documented.

The OSINT Search Agent researches online sources, social media and public databases at run time for each alert or case. No browser, desktop or computer control that an agent drives is documented.