Stuut automates the entire AR workflow—from outreach to payment collection—using a stack heavy on ML (PyTorch, TensorFlow, Transformers, RAG) and modern backend tooling (FastAPI, Node.js, Kubernetes). The engineering-first hiring profile (23 engineers across 40 open roles) paired with active projects in voice automation, ERP data pipelines, and invoice matching reveals a company building real-time cash-flow decision systems rather than simple AR workflow software.
Stuut is an AI platform that handles accounts receivable work autonomously for mid-market and enterprise businesses. The product integrates with ERPs (NetSuite, SAP, Oracle) and CRMs (HubSpot, Salesforce) to automate customer outreach, payment matching, and collections via voice and digital channels. Founded in 2024 and based in San Francisco, the company is 11–50 employees and actively hiring across engineering, sales, and data roles. Their focus is narrowly on AR automation rather than broader financial software, targeting the operational friction points in collections and cash application.
Stuut builds on PyTorch, TensorFlow, and Transformers for ML; FastAPI and Node.js for backend services; React and Vue for frontend; AWS, GCP, and Azure for cloud; and Snowflake, BigQuery, and Redshift for data warehousing. They integrate with ERP systems (NetSuite, SAP, Oracle) and CRMs (Salesforce, HubSpot).
Active projects include AI-powered cash-flow automation, voice automations for collections, ERP data pipeline design, intelligent invoice matching, and responsive B2B financial workflow applications. They are also building data infrastructure and account-based marketing programs.
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