Data discovery and compliance platform for sensitive data across hybrid environments
Ground Labs builds data discovery and remediation tools for privacy, security, and compliance—focused on finding sensitive data wherever it lives (servers, desktops, cloud). The tech stack (Go, Python, React, Kubernetes, ELK) reflects a mature backend-first architecture suited to scanning at scale. Current project velocity reveals a critical inflection: commercial launch of a new DSPM (Data Security Posture Management) SaaS platform alongside POC delivery and technical health checks. Hiring is accelerating but remains lean and engineering-forward (2 engineering roles, 1 product, 1 sales, 1 support), suggesting the org is prioritizing platform buildout and POC validation over sales expansion—typical for an on-premises vendor transitioning to SaaS.
Ground Labs is a 51–200-person data security company headquartered in Singapore, founded in 2007. The company specializes in discovering and remediating sensitive data (cardholder data, PII, payment card information) across multiple storage types and locations, serving enterprises managing GDPR, PCI, CCPA, PIPEDA, and Australian Privacy Act compliance. Their flagship products are Enterprise Recon and Card Recon. Currently, Ground Labs is executing a strategic shift: building a new DSPM SaaS platform from scratch while running technical POCs and health checks for existing customers. Sales operations and channel partner strategy are concurrent projects, indicating a parallel effort to scale go-to-market alongside product launch. The organization operates in Singapore with all active hiring localized to that region.
Ground Labs uses Go and Python for backend services, React/Vue/Angular for frontend, Kubernetes and Docker for containerization, Terraform for infrastructure, and ELK (Elasticsearch, Logstash, Kibana) for logging and observability. AWS, Azure, and GCP are in use for cloud deployment.
Ground Labs is launching a commercial DSPM (Data Security Posture Management) SaaS platform from scratch, running technical POCs and demos, building test automation and performance testing frameworks, designing channel partner strategy, and operationalizing sales forecasting. Development lifecycle bottlenecks and SaaS platform reliability are active focus areas.
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