Multilingual risk intelligence and entity resolution for government and enterprise
Babel Street runs a risk-intelligence platform built on Python, Scrapy and Playwright for web collection, Elasticsearch for search, and a GCP data layer (BigQuery, Airflow on Cloud Composer, Pub/Sub). LangChain, Hugging Face Transformers and PyTorch point to AI-driven entity matching. Accelerating hiring tilts toward sales, and job posts focus on channel partner programs and a Salesforce overhaul, signaling a push to scale indirect go-to-market.
Notable leadership hires: Mission Director
Babel Street is a privately held company founded in 2009 and headquartered in Washington, DC, with 201–500 employees. It provides risk intelligence to government, defense and private-sector organizations, helping them uncover hidden identities, assess vendor networks and detect threats. Core capabilities include multilingual and cross-lingual search, semantic analysis, social and traditional media monitoring, dark and deep web coverage, and entity resolution. The company operates under compliance frameworks including SOC 2, ISO/IEC 27001, CMMC and NIST CSF, and is hiring in the United States and Australia.
Babel Street uses Python, Java, Scrapy, Playwright, Elasticsearch, GCP (BigQuery, Cloud Run, Pub/Sub, Cloud Composer), Apache Airflow, Looker, PyTorch, Hugging Face Transformers, LangChain and Salesforce.
Yes, and hiring is accelerating. Sales leads the mix, with additional roles in engineering, data, design, security and support across the United States and Australia, including a Mission Director role.
Babel Street's stack references SOC 2, ISO/IEC 27001, CMMC and the NIST Cybersecurity Framework, consistent with serving government and defense customers.
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Babel Street'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.