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Kreditz Tech Stack
Open banking + AI credit decisioning for financial institutions
Kreditz automates credit and risk decisions by combining open banking data with machine learning on AWS. The stack is ML-first (SageMaker, scikit-learn, PyTorch, TensorFlow) paired with Go and Python for production workloads, and active projects reveal a company scaling toward enterprise: secure CI/CD, cloud governance design, and end-to-end ML pipelines. Hiring is accelerating across engineering and product while the leadership mix (CFO, head of product) signals a phase where capital efficiency and GTM execution matter as much as model accuracy.
Tech Stack 40 technologies
Core StackHubSpot AWS GitHub Actions Terraform Go Python Ruby SageMaker AWS Lambda scikit-learn pandas PyTorch TensorFlow Jira Docker gRPC JavaScript LinkedIn Google Analytics 4 SAST DAST AWS Fargate AWS Control Tower IAM AWS Step Functions Linear Git AWS ECS REST OpenAPI+10 more
What Kreditz Is Building
◆Challenges
- Scalable growth
- Profitability and efficiency
- Transform high-performing fintech into billion-dollar business
- Scaling marketing engine
- Driving pipeline and revenue
- Optimizing marketing automation
- Evolving cloud governance
- Automating ml pipelines
- Streamlining mlo ps processes
- Modernizing infrastructure
▲Active Projects
- Go-to-market & campaigns
- Seo and sem strategy
- Events & community
- Secure ci/cd pipelines in github actions
- Secure ecs fargate workloads
- Design guardrails for cloud governance
- End-to-end ml pipelines on aws
- Ml infrastructure using aws sage maker
- Instill best mlo ps practices
- Modernizing infrastructure
Hiring Activity
10 roles · 8 in 30d
Department
Seniority
Notable leadership hires: Chief Financial Officer
Company intelligence
