REGAL builds voice AI agents for customer support, sales and operations calls, running on a Python/TypeScript stack over AWS serverless and streaming services (Lambda, SQS, Kinesis, Fargate) with Twilio for telephony. Engineering pain points center on observability and quality evaluation for voice agents, while a sales-led, accelerating hiring mix targets mid-market expansion and complex enterprise deals.
REGAL is a New York-based, privately held company founded in 2020 that offers a platform for building, testing, deploying and monitoring autonomous AI agents for customer experience teams. Its focus is phone-based support, sales and operations conversations at consumer-facing businesses. The platform connects to a customer's first-party data and includes A/B testing tools for comparing AI agents against AI-assisted human agents. The company employs 51–200 people and hires in the United States across sales, engineering and product.
REGAL uses Python, TypeScript, Node.js, Nest.js, React and GraphQL on AWS (Lambda, SQS, Kinesis, Fargate, Aurora), with PostgreSQL, Redis, DynamoDB, Twilio, Terraform, Datadog, SageMaker, dbt and Looker.
Yes. Hiring is accelerating and weighted toward sales, with engineering and product roles as well, spanning junior through director levels in the United States.
REGAL is building observability tooling and evaluation frameworks for AI agents, developing a copilot product, deploying voice AI agents and expanding AI agent applications across customers.
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REGAL'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.
