Zeno builds an AI-driven research engine for legal teams using Python, Neo4j, Dagster, and Airflow to power identity graphs, entity resolution, and legal data pipelines. The stack reveals a data-infrastructure-first architecture: graph databases and workflow orchestration dominate, suggesting the core product depends on mapping complex legal relationships and documents. Hiring is weighted toward engineering (6) and data (3) roles across senior and staff levels, indicating they're scaling compute-intensive features rather than sales coverage—a signal that product-market fit in legal tech remains the priority over GTM velocity.
Zeno provides an intelligence platform for legal research and document analysis, built on generative AI and knowledge-graph infrastructure. Founded in 2023 and based in Rotterdam, the company serves modern legal teams and firms seeking to automate research workflows and extract actionable insights from unstructured legal information. Active projects span identity resolution, data ingestion pipelines, benchmarking datasets, and infrastructure for AI workloads, reflecting a focus on foundational engineering over feature breadth. Current pain points include scaling engineering capacity, controlling infrastructure costs, and addressing low AI adoption rates within traditional law firms—typical challenges for an early-stage legal-tech startup competing against embedded workflows.
Zeno's core stack includes Python, Neo4j (graph database), Dagster and Apache Airflow (workflow orchestration), SQL, Litestar and FastAPI (backends), Vue and React (frontends), plus AWS, Azure, GCP, Kubernetes, and Docker for infrastructure.
Zeno's active projects include identity graphs with merge/split semantics, entity resolution frameworks, scalable legal data pipelines, evaluation benchmarks for AI, backend services with Litestar, and Vue.js frontends, plus infrastructure for AI development and rapid scaling.
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