ML-driven document and data automation for alternative investments
Canoe Intelligence automates collection and extraction of alternative investment documents for allocators and wealth managers. Its ML stack goes beyond off-the-shelf APIs: PyTorch, TensorFlow, SageMaker, Modal, Weights & Biases plus LoRA/QLoRA/Unsloth point to in-house fine-tuning of models. Accelerating, sales-heavy hiring with a heavy ABM toolset (6sense, Demandbase, Outreach) and a new SRE practice signals a push to scale go-to-market and reliability together.
Notable leadership hires: Marketing Director
Canoe Intelligence is a New York-based, privately held company founded in 2017 that builds cloud software for managing alternative investment documents and data. Its platform uses machine learning to collect documents, extract data, and support data science work for institutional investors, asset servicers, capital allocators, family offices, endowments, pension funds, and wealth managers. The company originated inside a private investment firm before spinning out as a standalone vendor. It employs 51–200 people and hires in the United States and the United Kingdom.
Canoe runs Python, TypeScript and PHP on AWS with Docker and Kubernetes, stores data in Snowflake, PostgreSQL and MySQL, and trains models with PyTorch, TensorFlow, SageMaker, Modal and Weights & Biases.
Yes, hiring is accelerating, led by sales with data, engineering, marketing, ops and support roles, skewed toward senior and director levels, including a Marketing Director, in the United States and United Kingdom.
Canoe Intelligence is headquartered in New York, NY, and was founded in 2017. It has 51–200 employees and hires in the US and UK.
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Canoe Intelligence'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.