Sardine
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About
Sardine is a comprehensive AI-powered risk platform designed to detect and stop financial crime across the entire customer journey. It provides a unified infrastructure for fraud prevention, AML compliance, and automated risk decisioning. By integrating proprietary device intelligence with behavioral biometrics and data from over 40 enrichment providers, the platform helps organizations unmask high-risk users early—from the moment of account creation through to payment processing. The system is specifically built to handle modern, complex threats such as social engineering scams, authorized push payment (APP) fraud, and sophisticated account takeovers. The platform operates through a multi-layered approach, starting with a proprietary SDK that captures device signals and behavioral biometrics (DIBB). These signals are then processed through a feature warehouse containing over 4,800 risk-based attributes. A standout feature of the platform is its suite of specialized AI Agents, including the KYC Onboarding Agent and Sanctions Screening Agent. These agents are designed to scale team capacity by automating manual review tasks, such as resolving cultural name mismatches or inconsistent date formats, while providing detailed audit logs and decision validation for compliance teams. Sardine is primarily tailored for high-stakes financial environments, including leading banks, online retailers, and fintech companies like Coinbase, Revolut, and Novo. It is an ideal solution for compliance officers, fraud investigators, and engineering teams who need to consolidate siloed risk data into a single, real-time dashboard. Because the platform supports operations in over 150 countries and screens hundreds of billions in transaction volume, it is well-suited for global enterprises dealing with cross-border payments and complex international regulatory requirements. What distinguishes Sardine from traditional risk vendors is its "offense-first" philosophy and the continuous monitoring of session behavior. Unlike static tools that rely on one-time database checks, Sardine analyzes subtle patterns like suspicious mouse movements or the use of remote access tools throughout a user's session. Additionally, its "True Piercing" technology helps uncover the actual identity, location, and IP address of fraudsters who attempt to use advanced obfuscation techniques like VPNs or emulators, providing a level of visibility that standard fraud detection tools often lack.
Pros & Cons
Uniquely combines proprietary device signals and behavior biometrics in a single SDK.
Provides a massive feature warehouse with over 4,800 pre-built risk attributes.
Significantly reduces fraudulent chargebacks, with case studies showing rates as low as 0.003%.
Automates manual review workflows through specialized agentic AI for compliance.
Reveals true location and identity even when fraudsters use VPNs or emulators.
No public self-service pricing is available; all plans require a custom demo.
Integration requires the implementation of a proprietary SDK within the developer's application.
The platform's deep feature set may be overly complex for small-scale operations with simple risk profiles.
Use Cases
Fintech compliance officers can use the Sanctions Screening Agent to automatically resolve name mismatches and generate audit logs for PEP and adverse media alerts.
Fraud investigators at online retailers can detect bot-led account takeovers by identifying non-human mouse movements and suspicious copy-paste behaviors.
Operations managers at neobanks can utilize the Disputes Agent to automate the gathering of data and evidence for filing chargeback responses to processors.
Risk engineering teams can leverage the feature warehouse to train custom ML models on Snowflake and run them within Sardine's real-time risk engine.
Onboarding teams can use the KYC Agent to reduce manual reviews by resolving inconsistencies in date formats and identity data across different cultures.
Platform
Task
Features
• case management
• device intelligence
• behavioral biometrics
• no-code rules editor
• true piercing unmasking
• aml monitoring
• sanctions screening agent
• kyc onboarding agent
FAQs
What types of financial crime does Sardine help prevent?
Sardine is designed to detect and stop identity fraud, payment fraud, account takeovers (ATO), money laundering, and social engineering scams like authorized push payment (APP) fraud.
How do Sardine's AI Agents assist fraud teams?
AI Agents automate time-consuming manual tasks like resolving KYC mismatches, reviewing sanctions alerts, and preparing evidence packages for chargeback disputes to match processor requirements.
Can I integrate my own machine learning models into the platform?
Yes, Sardine provides a model garden infrastructure that allows you to train your own models via GCP or Snowflake and run them using their extensive feature warehouse.
What is 'True Piercing' technology?
True Piercing is an advanced detection feature that unmasks fraudsters using VPNs, emulators, or remote access tools to reveal their true identity, location, IP, and operating system.
Does the platform support global operations?
Sardine supports businesses in over 150 countries and integrates with over 40 data providers for phone, email, SSN, and banking data enrichment across the globe.
Pricing Plans
Enterprise
Unknown Price• Proprietary Device & Behavior SDK
• KYC and KYB Verification
• AML Transaction Monitoring
• AI Agents for Manual Review
• Real-time Risk Engine
• Access to 4,800+ Risk Features
• Sanctions Screening
• Case Management Dashboard
• Fraud Consortium Access (Sonar)
• Global Coverage (150+ Countries)
Job Opportunities
DevOps Engineer
Stop financial crime and automate risk decisioning with real-time fraud prevention, behavioral biometrics, and AI agents designed for banks and fintech teams.
Benefits:
Generous compensation in cash and equity
Early exercise for all options
Flexible paid time off and Year-end break
Health insurance, dental, and vision
4% matching in 401k / RRSP
Experience Requirements:
6+ years of experience in DevOps, SRE, or software engineering roles
Other Requirements:
Proficiency in Python or Go
Experience with Kubernetes, ArgoCD, Helm, and Terraform
Familiarity with GCP
Hands-on experience with observability tools like Prometheus or Datadog
Responsibilities:
Own and evolve DevOps and platform engineering function
Design and maintain secure, scalable CI/CD pipelines
Improve observability via Datadog, GCP, and custom dashboards
Implement and maintain FinOps governance
Enable developer productivity by creating internal tooling
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Go Backend Engineer
Stop financial crime and automate risk decisioning with real-time fraud prevention, behavioral biometrics, and AI agents designed for banks and fintech teams.
Benefits:
Generous compensation in cash and equity
Early exercise for all options
Work from anywhere: Remote-first Culture
Flexible paid time off
MacBook Pro
Experience Requirements:
2–3+ years of commercial backend development experience
Other Requirements:
Deep understanding of Go
Strong experience with various databases (SQL & NoSQL)
Hands-on experience with public clouds (AWS or GCP)
Experience building distributed systems
Responsibilities:
Design and implement high-performance microservices using Go
Analyze and improve efficiency of infrastructure
Define architectural patterns for database usage and API design
Work with Cloud environments for resilience and security
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Machine Learning Engineer
Stop financial crime and automate risk decisioning with real-time fraud prevention, behavioral biometrics, and AI agents designed for banks and fintech teams.
Benefits:
Generous compensation in cash and equity
Early exercise for all options
Flexible paid time off
Health insurance coverage
Annual health and wellness stipend
Education Requirements:
Bachelor's or Master's in Computer Science, Engineering, or a related discipline
Experience Requirements:
5+ years in software engineering
Backend experience in Go or Python
Hands-on experience with applied ML using large datasets
Other Requirements:
Strong SQL skills
Experience with feature pipelines and model deployment
Excellent communication skills in English
Responsibilities:
Build and optimize data pipelines and backend services
Develop and deploy ML models for fraud detection
Turn raw data into production-ready features
Collaborate with platform and backend engineers
Maintain high standards of security and compliance
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Ratings & Reviews
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