Inside Wraxel’s product engineering methodology. We combine test-driven development, automated MLOps CI/CD pipelines, zero-trust security, and high-throughput cloud infrastructure.
Our engineering practices ensure high maintainability, rapid deployment velocity, and zero production regressions.
Enforcing domain-driven design, modular microservices, 90%+ unit test coverage, and static code analysis (SonarQube) on every commit.
Continuous model integration, dataset versioning (MLflow), automated vLLM inference deployments, and real-time model drift monitoring.
Embedding security directly into CI/CD workflows: mandatory PII data masking, automated dependency vulnerability scans, and Okta RBAC.
Multi-region Kubernetes (EKS/GKE) orchestration, automated Terraform infrastructure-as-code, and auto-scaling NVIDIA GPU pools.
Sub-second real-time event streaming with Apache Kafka, dbt data transformations, and high-performance Snowflake/BigQuery query indexing.
Comprehensive APM telemetry with Datadog, Prometheus, and Grafana to detect anomalies and trigger automated incident resolution.
Battle-tested frameworks and cloud technologies powering our enterprise solutions.
Our 4-stage sprint methodology guarantees rapid execution without compromising stability or security.
Database schema design, API contract definition, zero-trust threat modeling, and team sprint planning.
Weekly production sprint releases, pair programming, TDD unit tests, and automated static analysis.
Automated vulnerability scanning, SSL/TLS security hardening, Okta SSO integration, and code review.
Zero-downtime canary deployments, real-time APM telemetry monitoring, and automated scaling.
Everything you need to know about Wraxel’s Product Engineering Culture.