DevOps Services for Startups
Build the Right Foundation from Day One
We help startups lay a strong technical foundation that grows with the business. Whether you’re building your first MVP or scaling to thousands of users, we ensure your infrastructure is:
- Reliable — production-grade environments that reduce downtime and risks
- Scalable — ready to support growth without constant rework
- Secure — meeting compliance and data protection needs from the start
- Efficient — keeping cloud and operations costs under control
Our packages are designed specifically for software startups and AI-driven startups, combining cloud engineering, DevOps automation, and MLOps expertise. With our support, your developers stay focused on product innovation, while we take care of the pipelines, environments, and monitoring that keep your product running smoothly.
In short: we give you enterprise-level infrastructure at startup speed and budget—so you can launch faster, scale smarter, and build trust with your users and investors.
Packages for Software Startups
🚀 Launch Package — 0 → 1
For teams starting from scratch that need an environment ready for development, testing, and production.
Deliverables:
- Cloud infrastructure setup (AWS, Azure, or GCP) with IaC principles
- Git-based version control (GitHub/GitLab) with branching strategy
- CI/CD pipeline setup (build, test, deploy automation)
- Docker containerization and basic orchestration
- Separate staging and production environments
- Monitoring dashboards for uptime, performance, and errors
- Security essentials (SSL, IAM roles, secrets management)
- Documentation and knowledge transfer
⏱ Timeline: 2–4 weeks
🔄 Optional Retainer: Cloud monitoring, updates, on-call DevOps support
⚙️ Optimization & Maintenance Package
For startups that already run infrastructure but want it to be faster, safer, and more cost-effective.
Deliverables:
⏱ Timeline: 2–3 weeks audit + monthly retainer
🔄 Optional Retainer: 24/7 monitoring and DevOps support
For startups that already run infrastructure but want it to be faster, safer, and more cost-effective.
Deliverables:
- Comprehensive audit of existing cloud, pipelines, and deployments
- CI/CD optimization (shorter builds, fewer failures)
- Cloud cost optimization and billing transparency
- Enhanced monitoring and logging (Grafana, ELK, Datadog)
- Security hardening (identity, secrets, firewalls, compliance)
- Documentation cleanup and process standardization
- Ongoing maintenance (patching, scaling, monitoring)
⏱ Timeline: 2–3 weeks audit + monthly retainer
🔄 Optional Retainer: 24/7 monitoring and DevOps support
Packages for AI Startups
🤖 AI Launch Package — AI-Ready Infrastructure from Scratch
For AI/ML startups that require GPU-enabled infrastructure and MLOps pipelines from the beginning.
Deliverables:
- GPU-enabled cloud environment (AWS Sagemaker, GCP Vertex AI, Azure ML)
- Secure data storage (S3/Blob/GCS) with access control policies
- Git + dataset versioning (Git LFS, DVC)
- MLOps pipeline: data ingestion → model training → testing → deployment
- Model serving endpoints (Kubernetes or managed services)
- Dashboards for infrastructure and model performance monitoring
- GPU cost-control setup (quotas, autoscaling)
- Compliance and security (GDPR, HIPAA if required)
- Documentation and training session with your team
⏱ Timeline: 3–5 weeks
🔄 Optional Retainer: Retraining automation, model drift monitoring, GPU cost optimization
⚙️ AI Optimization & Maintenance Package
For AI startups already running models in production who need reliability and efficiency at scale.
Deliverables:
⏱ Timeline: 2–3 weeks audit + monthly retainer
🔄 Optional Retainer: 24/7 monitoring, compliance support, and pipeline optimization
For AI startups already running models in production who need reliability and efficiency at scale.
Deliverables:
- Audit of AI infrastructure and MLOps pipelines
- GPU cost optimization (scheduling, spot instances, autoscaling)
- Advanced MLOps (experiment tracking, retraining pipelines)
- Model monitoring (accuracy, drift, latency)
- Data governance and compliance (GDPR, HIPAA)
- Continuous training and deployment for ML models (CT/CD)
- Documentation and onboarding materials for new engineers
- Ongoing MLOps support
⏱ Timeline: 2–3 weeks audit + monthly retainer
🔄 Optional Retainer: 24/7 monitoring, compliance support, and pipeline optimization
Why Startups Choose Us
- Technical depth — we integrate with your engineering team, not just deliver “black-box” solutions
- Startup experience — we understand the trade-offs between speed, cost, and long-term scalability
- Growth ready — environments we build are designed to evolve with your product and team size
Not sure which package to chose?