Regal builds a voice AI agent platform targeting enterprise contact centers. The stack is heavily AWS-native (Fargate, Lambda, SageMaker, Kinesis) with Python/TypeScript backends and modern observability (Datadog, CloudWatch), reflecting a company optimizing for low-latency agent deployment at scale. Active hiring is sales-heavy (4 open roles) alongside smaller engineering and data teams, paired with pain points around SLA adherence and observability gaps — a pattern suggesting Regal is scaling customer acquisition while maturing production reliability.
Tech Stack 31 technologies
Core StackAWS AWS Lambda Terraform Python TypeScript DynamoDB Datadog SageMaker dbt Looker Salesforce Salesloft ZoomInfo React Nest.js GraphQL PostgreSQL Redis Twilio Node.js AWS Fargate Bash Aurora OpenSearch Kinesis AWS SQS BullMQ AWS CloudWatch LinkedIn Sales Navigator
What REGAL Is Building
◆Challenges
- Meeting sla adherence
- Improving support processes
- Automating deployment and observability
- Scaling ai workloads
- Enabling self-service developer environments
- Accelerating customer deployments
- Lack of intuitive observability
- Customers can't see agent performance
- Complex sales cycles
- Closing enterprise deals
▲Active Projects
- Voice agent platform
- Infrastructure as code provisioning
- Internal developer platform
- Voice ai agent deployment
- Ai agent voice prompt creation
- Custom function development
- Qa testing and tooling
- Transform observability
- Define measurement framework
- Ship polished data experiences
Hiring Activity
15 roles · 10 in 30d
Department
Seniority
Company intelligence
