Sardine
Agentic fraud and AML platform
Sardine’s current platform spans fraud prevention, device and behavioral signals, KYC, KYB, AML monitoring, case management, and agent-assisted operations. Its published agent set includes business due diligence, screening, graph analysis, and SAR generation. It is a broader-suite candidate even though the original list places it only under fraud.
Our assessment
Add it to the cross-domain evaluation set. Confirm the exact depth of underwriting and filing.
Best fit and limitations
A serious broader-suite candidate for fintech and payment risk teams that need device intelligence, onboarding, and ongoing fraud/AML operations connected.
- Do not assume all identity or business data is proprietary or included.
- Credit underwriting workflows are documented. Merchant reserves, settlement execution, and network exposure controls still need separate proof.
- A SAR generation agent does not prove automated submission in every jurisdiction.
Tools 6
Device and behaviorEarly fraud detection+
- Device, emulator, bot, and behavioral risk signals
- Context from onboarding through payment activity
Fraud and transaction riskPayment controls+
- Real-time fraud and transaction monitoring
- Combine customer, device, and outcome context
KYC onboardingIdentity orchestration+
- Risk-adaptive verification and step-up checks
- Use as a workflow layer or alongside existing vendors
Global KYBBusiness due diligence+
- Business verification and beneficial ownership context
- Configurable policies and business research agents
Credit UnderwritingCredit decision workflows+
- Consumer, business, and seller-financing policies
- Combine bureau, cash-flow, identity, and fraud data; test decisions in shadow mode
AML operations + AI agentsInvestigations and reporting+
- Screening, cases, and transaction monitoring
- OSINT, graph, sanctions, PEP, and SAR agent roles
AI capabilities
Predictive fraud + specialized risk agents
Sardine lists agents for rule help, data analysis, due diligence, screening, transaction review, and SAR generation. Each has a different evidence and approval requirement.
What to validate
Test each selected agent separately. Require source-linked findings, permission limits, escalation on uncertainty, and approval before high-impact actions.
Implementation
Integration checklist
- Join SDK signals, customer records, businesses, and payment events.
- Test latency, session availability, case creation, and downstream payment actions.
- Clarify direct versus orchestrated data providers and export rights.
Commercial scope
Quote required. Separate device/behavior events, fraud scoring, verification data, AML, cases, agents, and reporting.
Estimate total costQuestions for the demo
- Which functions remain with partners, and what are their extra costs?
- What incremental fraud capture comes from device and consortium signals?
- Can every AI-generated finding be traced back to source evidence?
Sources 4
Reviewed September 17, 2026. Product claims come from public sources. Fit, limits, and evaluation questions are our analysis. This is not a hands-on performance test. Methodology
