AI-powered document fraud detection for lending, KYC, and compliance
Resistant AI detects forged and manipulated documents across bank statements, IDs, pay stubs, and tax forms using a machine-learning system deployed on AWS (Lambda, DynamoDB, Aurora, Athena). The company has analyzed 170M+ documents and serves 8K+ fraud analysts. Current hiring is engineering-heavy (3 of 7 open roles) with a focus on backend/frontend platform development, partner enablement, and customer success operations—indicating a shift toward scaling via integrations and reducing churn rather than pure product innovation.
Notable leadership hires: Customer Success Lead
Resistant AI provides document fraud detection for financial services workflows: digital lending, loan underwriting, KYC onboarding, merchant screening, tenant vetting, and insurance claims. The platform processes documents in all formats (PDFs, images) and languages, returning verdicts in under 20 seconds with 99% accuracy. Customers include lenders, fintech platforms, and compliance teams. The company was founded in 2019, is based in New York, and employs 51–200 people. Internally, teams are addressing partner churn, inconsistent playbooks, and unstructured IT support—problems typical of early-stage SaaS scaling beyond product-market fit.
AWS (Lambda, DynamoDB, Aurora, Athena, API Gateway, CDK), Python, TypeScript, FastAPI, Vue, Docker, GitLab, Okta, HubSpot, Salesforce, and Sentry.
Yes. 3 of 7 active roles are engineering (mid-level and senior), focused on backend and frontend SaaS platform development. Also hiring sales, marketing, and customer success in Czechia.
Over 170 million documents for fraud detection, with 8,000+ fraud and compliance analysts using the platform.
Resistant AI - Fraud Detection's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.