AI document intake and data extraction for legal and claims teams
Foundation AI automates inbound document handling for law firms and insurance claims departments, classifying, routing and extracting data from mail and email. Its stack pairs transformer models (BERT, RoBERTa, GPT, LangChain, LlamaIndex) with pipeline tooling like Airflow, Celery and RabbitMQ, and heavy observability (Datadog, Splunk, New Relic). Accelerating, junior-weighted hiring in India and Brazil centers on reliability and incident handling, pointing to a scaling production platform.
Foundation AI, founded in 2019 and headquartered in Irvine, California, builds software that automates document intake for legal and claims organizations. The platform matches incoming documents to the correct claim or matter, identifies document type, pulls out key fields, files documents into the customer's document management system, notifies the responsible staff member, and pushes data into downstream systems. It applies OCR, natural language processing and large language models to mailroom and classification work. The company is privately held and employs 51–200 people.
Foundation AI runs Python, FastAPI, Flask, PostgreSQL, Docker, Kubernetes and AWS, with Airflow, Celery and RabbitMQ for pipelines and BERT, RoBERTa, GPT, PyTorch, LangChain and LlamaIndex for AI models.
Foundation AI is hiring in India and Brazil, with hiring accelerating and focused mainly on engineering, plus operations and support roles, largely at junior level.
Foundation AI, based in Irvine, California, automates document intake for law firms and claims departments, classifying, routing, extracting data from and filing inbound mail and email documents.
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Foundation AI'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 →
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