Verbit builds AI transcription and captioning backed by human transcribers, with a stack centered on Python, PyTorch and TensorFlow running across AWS, GCP and Azure. LLM tooling like RAG, Langfuse and LiteLLM, plus active work on agentic flows and an AI litigation ecosystem, shows the company pushing beyond ASR into legal-workflow intelligence. Hiring is minimal and engineering-only, concentrated in Ukraine.
Verbit, founded in 2017 and headquartered in New York, NY, provides AI-driven transcription, captioning and related speech products. It serves speech-heavy sectors including education, enterprise, live media events and legal proceedings, where its Legal Visor product supports litigators in real time. The company combines machine transcription with human transcriber review. It is privately held with 201–500 employees.
Verbit uses Python, PyTorch and TensorFlow for ML, FastAPI, Flask and gRPC services, React and TypeScript on the front end, PostgreSQL and DynamoDB for data, and runs on AWS, GCP and Azure.
Yes, but hiring is minimal. Current openings are in engineering only, at mid and senior levels, and are based in Ukraine.
Verbit is building ML model deployment pipelines, optimizing ASR integration, integrating LLM agentic flows, and developing an AI-driven litigation ecosystem alongside its transcription engine workflows.
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Verbit.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 →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.
